In the past decade, interdisciplinary research has revealed the potential benefits of using social robots in the care of individuals with autism. There is a growing interest in integrating social robots into clinical practice. However, while significant efforts have been made to develop and test the technical aspects, clinical validation and implementation lag behind. This article presents a systematic literature review from a clinical perspective, focusing on articles that demonstrate clinical relevance through experimental studies. These studies are analysed and critically discussed in terms of their integration into healthcare and care practices. The goal is to assist healthcare professionals in identifying opportunities and limitations in their practice and to promote further interdisciplinary cooperation.

Difficulties in processing emotional facial expressions is considered a central characteristic of children with autism spectrum condition (ASC). In addition, there is a growing interest in the use of virtual avatars capable of expressing emotions as an intervention aimed at improving the social skills of these individuals. One potential use of avatars is that they could enhance facial recognition and guide attention. However, this aspect needs further investigation. The aim of our study is to assess differences in eye gaze processes in children with ASC when they see avatar faces expressing emotions compared to real faces. Eye-tracking methodology was used to compare the performance of children with ASC between avatar and real faces. A repeated-measures general linear model was adopted to understand which characteristics of the stimuli could influence the stimuli’s fixation times. Survival analysis was performed to understand differences in exploration behaviour between avatar and real faces. Differences between emotion recognition accuracy and the number of fixations were evaluated through a paired t-test. Our results confirm that children with autism have higher capacities to process and recognize emotions when these are presented by avatar faces. Children with autism are more attracted to the mouth or the eyes depending on the stimulus type (avatar or real) and the emotion expressed by the stimulus. Also, they are more attracted to avatar faces expressing negative emotions (anger and sadness), and to real faces expressing surprise. Differences were not found regarding happiness. Finally, they show a higher degree of exploration of avatar faces. All these elements, such as interest in the avatar and reduced attention to the eyes, can offer important elements in planning an efficient intervention.

The differential diagnosis between schizophrenia spectrum disorders (SSD) and autism spectrum disorders (ASD) remains an important clinical question, because they have overlap in clinical diagnosis. This study explored the differences between ASD (n = 44) and SSD patients (n = 59), compared to typically developing peers (n = 63), in completing an advanced Theory of Mind (ToM) task. The outcome found several differences between groups. The SSD patients showed greater difficulty in understanding social scenarios, while ASD individuals understood the stories, but did not correctly identify the protagonist’s intention. The interesting aspect of the results is that some ToM stories are more informative about the mentalistic reasoning of the two clinical groups, namely, the stories that investigate pretend, persuasion, double bluff and ironic joke constructs.

Autism spectrum disorder (ASD) is a set of heterogeneous neurodevelopmental conditions, characterised by difficulties in social communication and restricted, repetitive behaviours and interests. Th...

Background: Autism spectrum disorder (ASD) is characterized by an impairment in social cognition (SC). SC is a cognitive construct that refers to the capacity to process information about social situations. It is a complex network that includes distinct components. Exploring how SC components work together leads to a better understanding of how their interactions promote adequate social functioning. Our main goal was to use a novel statistical method, graph theory, to analyze SC relationships in ASD and Typically Developing (TD) individuals.Methods: We applied graph theory to SC measures to verify how the SC components interact and to establish which of them are important within the interacting SC network for TD and ASD groups.Results: The results showed that, in the TD group, the SC nodes are connected; their network showed increased betweenness among nodes, especially for the Theory of Mind. By contrast, in the SC network in the ASD group the nodes are highly disconnected, and the efficient connection among the components is absent.Conclusion: ASD adults do not show SC competencies and functional communication among these skills. Under this regard, specific components are crucial, suggesting they could represent critical domains for ASD SC.

Background: Numerous user-related psychological dimensions can significantly influence the dynamics between humans and robots. For developers and researchers, it is crucial to have a comprehensive understanding of the psychometric properties of the available instruments used to assess these dimensions as they indicate the reliability and validity of the assessment. Objective: This study aims to provide a systematic review of the instruments available for assessing the psychological aspects of the relationship between people and social and domestic robots, offering a summary of their psychometric properties and the quality of the evidence. Methods: A systematic review was conducted following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines across different databases: Scopus, PubMed, and IEEE Xplore. The search strategy encompassed studies meeting the following inclusion criteria: (1) the instrument could assess psychological dimensions related to social and domestic robots, including attitudes, beliefs, opinions, feelings, and perceptions; (2) the study focused on validating the instrument; (3) the study evaluated the psychometric properties of the instrument; (4) the study underwent peer review; and (5) the study was in English. Studies focusing on industrial robots, rescue robots, or robotic arms or those primarily concerned with technology validation or measuring anthropomorphism were excluded. Independent reviewers extracted instrument properties and the methodological quality of their evidence following the Consensus-Based Standards for the Selection of Health Measurement Instruments guidelines. Results: From 3828 identified records, the search strategy yielded 34 (0.89%) articles that validated and examined the psychometric properties of 27 instruments designed to assess individuals’ psychological dimensions in relation to social and domestic robots. These instruments encompass a broad spectrum of psychological dimensions. While most studies predominantly focused on structural validity (24/27, 89%) and internal consistency (26/27, 96%), consideration of other psychometric properties was frequently inconsistent or absent. No instrument evaluated measurement error and responsiveness despite their significance in the clinical context. Most of the instruments (17/27, 63%) were targeted at both adults and older adults (aged ≥18 years). There was a limited number of instruments specifically designed for children, older adults, and health care contexts. Conclusions: Given the strong interest in assessing psychological dimensions in the human-robot relationship, there is a need to develop new instruments using more rigorous methodologies and consider a broader range of psychometric properties. This is essential to ensure the creation of reliable and valid measures for assessing people’s psychological dimensions regarding social and domestic robots. Among its limitations, this review included instruments applicable to both social and domestic robots while excluding those for other specific types of robots (eg, industrial robots).