Research in the area of robotics has made available numerous possibilities for further innovation in the education of children, especially in the rehabilitation of those with learning difficulties and/or intellectual disabilities. Despite the scientific evidence, there is still a strong scepticism against the use of robots in the fields of education and care of people. Here we present a study on the acceptance of robots by experienced practitioners (specialized in the treatment of intellectual disabilities) and university students in psychology and education sciences (as future professionals). The aim is to examine the factors, through the Unified Theory of Acceptance and Use of Technology (UTAUT) model, that may influence the decision to use a robot as an instrument in the practice. The overall results confirm the applicability of the model in the context of education and care of children, and suggest a positive attitude towards the use of the robot. The comparison highlights some scepticism among the practitioners, who perceive the robot as an expensive and limited tool, while students show a positive perception and a significantly higher willingness to use the robot. From this experience, we formulate the hypothesis that robots may be accepted if more integrated with standard rehabilitation protocols in a way that benefits can outweigh the costs.

The concept of sustainability, from a psychological point of view, can be related to the promotion of personal resources that help people to find decent and meaningful work and live quality lives. In the psychological concept of sustainability and sustainable development, the sustainability of careers is related not only to individual career management, but also to the possibility for individuals to obtain a good quality of life despite the frequent changes and the unpredictability of the work context. The present study focuses on the constructs of self-perceived employability and meaningful work, analyzing their relationships with workers’ quality of life. An empirical study was conducted on 660 Italian workers using the following measures: Self-perceived employability scale, work and meaning inventory, courage measure, satisfaction with life scale, and the flourishing scale. The results showed direct effects of employability and meaningful work on the indicators of quality of life (life satisfaction and flourishing); moreover, indirect effects of employability and meaningful work on the quality of life were found to be caused by the mediation of courage.

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Recent studies suggest that some children with autism prefer robots as tutors for improving their social interaction and communication abilities which are impaired due to their disorder. Indeed, research has focused on developing a very promising form of intervention named Robot-Assisted Therapy. This area of intervention poses many challenges, including the necessary flexibility and adaptability to real unconstrained therapeutic settings, which are different from the constrained lab settings where most of the technology is typically tested. Among the most common impairments of children with autism and intellectual disability is social attention, which includes difficulties in establishing the correct visual focus of attention. This article presents an investigation on the use of novel deep learning neural network architectures for automatically estimating if the child is focusing their visual attention on the robot during a therapy session, which is an indicator of their engagement. To study the application, the authors gathered data from a clinical experiment in an unconstrained setting, which provided low-resolution videos recorded by the robot camera during the child-robot interaction. Two deep learning approaches are implemented in several variants and compared with a standard algorithm for face detection to verify the feasibility of estimating the status of the child directly from the robot sensors without relying on bulky external settings, which can distress the child with autism. One of the proposed approaches demonstrated a very high accuracy and it can be used for off-line continuous assessment during the therapy or for autonomously adapting the intervention in future robots with better computational capabilities.

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The fear of contagion during the COVID-19 pandemic has been indicated as a relevant cause of psychological pathologies occurring in this period. Food represents a compensating experience, distracting from the experiences of uncertainty, fear and despair, causing alterations in eating habits and behaviors. The study aims at evaluating the relations between fear of a pandemic, mood states and eating disorders in Italian college students, taking into account gender differences. During the lockdown for the pandemic, a sample of 469 college students equally distributed by gender, was recruited online using a questionnaire including the FCV-19S for the assessment of fear of COVID-19, the profile of mood states (POMS) for the evaluation of different emotional states, the eating disorder inventory-2 (EDI-2) and the binge eating scale (BES) to evaluate the presence of the levels of eating disorders. As expected, all emotive states measured by POMS (tension, depression, anger, tiredness, confusion) resulted significantly correlated with the fear of COVID-19. Women were more exposed to fear of COVID-19 showing greater tension, fatigue, depression and confusion, and a significantly higher total mood disturbance score than males. Regarding the EDI-2 and BES variables, tension and anxiety resulted significantly correlated also with bulimic behavior, while depression with interoceptive awareness, impulsivity, and binge eating behaviors, without gender differences. In conclusion, the negative impact of the fear of COVID-19 on the emotional profile and eating behavior suggests the need to implement strategies against psychological distress during the pandemic emergency, and to design psycho-educational interventions aimed at modifying the lifestyle for preventing risks of mental disorders fostering health-oriented behaviors.

Major depressive disorder (MDD) is a severe mental illness that affects 5-20% of the general population. Current antidepressant drugs exert only a partial clinical efficacy because approximately 30% of depressed patients failed to respond to these drugs and antidepressants produce remission only in 30% of patients. This can be explained by the fact that the complex pathophysiology of depression has not been completely elucidated, and treatments have been mainly developed following the "monoaminergic hypothesis" of depression without considering the key role of other factors involved in the pathogenesis of MDD, such as the role of chronic stress and neuroinflammation. Chronic stress acts as a risk factor for the development of MDD through the impairment of neurotrophins signaling such as brain-derived neurotrophic factor (BDNF) and transforming-growth-factor-β1 (TGF-β1). Stress-induced depressive pathology contributes to altered BDNF level and function in MDD patients and, thereby, an impairment of neuroplasticity at the regional and circuit level. Recent studies demonstrate that aerobic exercise strongly increases BDNF production and it may contribute as a non-pharmacological strategy to improve the treatment of cognitive and affective symptoms in MDD. Here we will provide a general overview on the possible synergism between physical activity and antidepressants in MDD. Physical activity can synergize with antidepressant treatment by rescuing neurotrophins signaling in MDD patients, promoting neuronal health and recovery of function in MDD-related circuits, finally enhancing pharmacotherapeutic response. This synergism might be particularly relevant in elderly patients with late-life depression, a clinical subgroup with an increased risk to develop dementia.

Evidence from developmental as well as neuroscientific studies suggest that finger counting activity plays an important role in the acquisition of numerical skills in children. It has been claimed that this skill helps in building motor-based representations of number that continue to influence number processing well into adulthood, facilitating the emergence of number concepts from sensorimotor experience through a bottom-up process. The act of counting also involves the acquisition and use of a verbal number system of which number words are the basic building blocks. Using a Cognitive Developmental Robotics paradigm we present results of a modeling experiment on whether finger counting and the association of number words (or tags) to fingers, could serve to bootstrap the representation of number in a cognitive robot, enabling it to perform basic numerical operations such as addition. The cognitive architecture of the robot is based on artificial neural networks, which enable the robot to learn both sensorimotor skills (finger counting) and linguistic skills (using number words). The results obtained in our experiments show that learning the number words in sequence along with finger configurations helps the fast building of the initial representation of number in the robot. Number knowledge, is instead, not as efficiently developed when number words are learned out of sequence without finger counting. Furthermore, the internal representations of the finger configurations themselves, developed by the robot as a result of the experiments, sustain the execution of basic arithmetic operations, something consistent with evidence coming from developmental research with children. The model and experiments demonstrate the importance of sensorimotor skill learning in robots for the acquisition of abstract knowledge such as numbers.