Robot-Assisted Autism Therapy (RAAT). Criteria and Types of Experiments Using Anthropomorphic and Zoomorphic Robots. Review of the Research

Psychological variables related to technology-mediated intervention design in autism spectrum disorder

BACKGROUND

Autism spectrum disorder (ASD) is a lifelong neurodevelopmental disorder characterized by persistent impairments in communication, social interaction and learning (Hodges et al., 2020). Because of its heterogeneous nature, ASD presents complex challenges, including social exclusion, school abandonment and limited access to health care. Technologies offer a pragmatic solution to overcome these limitations and to deliver therapeutic interventions in both physical and online environments. Studies have demonstrated that technology-mediated interventions (TMIs) have a positive impact on the development of capabilities of individuals with ASD. However, according to the European Parliament's Research Service technologies for ASDs are less mature (European Parliament. Directorate General for Parliamentary Research Services., 2018) and the causes and effects of TMIs in ASD should be better understood.

AIMS

Present study aimed to investigate the psychological variables related to TMIs in ASD.

METHODS AND PROCEDURES

The study employed a survey research method with a between-subjects design involving 61 adult participants comprising therapists, teachers and parents of children with ASD and it examined psychological variables related to children with ASD, factors of technology usage, and parental and educators' experiences.

OUTCOMES AND RESULTS

The analysis of the data obtained from the questionnaire focused on correlations and differences between groups, and was carried out using nonparametric tests. Kendall's Tau B test was used to explore the relationships between variables. The Mann-Whitney nonparametric test was employed to identify differences between groups.

CONCLUSIONS AND IMPLICATIONS

The findings revealed numerous relationships between variables and meaningful differences between the groups investigated in terms of how technologies are perceived by stakeholders involved in ASD interventions.

Assisted Robots in Therapies for Children with Autism in Early Childhood

Children with autism spectrum disorder (ASD) have deficits that affect their social relationships, communication, and flexibility in reasoning. There are different types of treatment (pharmacological, educational, psychological, and rehabilitative). Currently, one way to address this problem is by using robotic systems to address the abilities that are altered in these children. The aim of this review will be to analyse the effectiveness of the incorporation of the different robotic systems currently existing in the treatment of children up to 10 years of age diagnosed with autism. A systematic review has been carried out in the PubMed, Scopus, Web of Science, and Dialnet databases, with the following descriptors: child, autism, and robot. The search yielded 578 papers, and nine were selected after the application of the PRISMA guideline. The quality of the studies was analysed with the PEDRo scale, and only those with a score between four and six were selected. From this study, the conclusion is that the use of robots, in general, improves children's behaviour in the short term, but longer-term experiences are necessary to achieve more conclusive results.

People with Autism Spectrum Disorder Could Interact More Easily with a Robot than with a Human: Reasons and Limits

Individuals with Autism Spectrum Disorder show deficits in communication and social interaction, as well as repetitive behaviors and restricted interests. Interacting with robots could bring benefits to this population, notably by fostering communication and social interaction. Studies even suggest that people with Autism Spectrum Disorder could interact more easily with a robot partner rather than a human partner. We will be looking at the benefits of robots and the reasons put forward to explain these results. The interest regarding robots would mainly be due to three of their characteristics: they can act as motivational tools, and they are simplified agents whose behavior is more predictable than that of a human. Nevertheless, there are still many challenges to be met in specifying the optimum conditions for using robots with individuals with Autism Spectrum Disorder.

Assistive technology to facilitate children's play: a scoping review

PURPOSE

Play is a fundamental human right and one of the most important occupations in children's lives. Fewer opportunities exist for children with physical disabilities (CWPD) to play. This study aimed to conduct a scoping review of published peer-reviewed literature on using AT to enable "play-for-the-sake-of-play" by CWPD.

METHOD

The review was conducted using a widely accepted scoping review methodology. Literature searches were conducted from January 2000 to March 2022 using MEDLINE, Central, CINAHL, ERIC, Scopus, and EMBASE. Pairs of reviewers used an online systematic review system to manage title, abstract, and full-text screening. Excel was used for data extraction and charting. Data was charted based on type of AT, play types according to LUDI definitions, and level of evidence.

RESULTS

The search yielded 5250 papers after the removal of duplicates. Title and abstract screening identified 58 studies for full-text screening. The final sample included 31 papers. Seven types of AT were identified in studies: power mobility, virtual reality, robots, adaptations for upper limb differences, switch-adapted games, augmentative and alternative communication devices, and mobility aids. Twenty-three papers addressed cognitive play, seven addressed social play, and one addressed both cognitive and social play. Most studies used case study, descriptive, or repeated measures designs.

CONCLUSION

There is limited evidence regarding the use of AT to support play-for-the-sake-of-play in CWPD. Given the importance of play, further research using rigorous methodologies and the development of assistive technology dedicated to promoting play-for-the-sake-of-play is warranted.

Measuring Engagement in Robot-Assisted Therapy for Autistic Children

Children with autism face a range of challenges when it comes to verbal and nonverbal communication. It is essential that children participate in a variety of social, educational, and therapeutic activities to acquire knowledge that is essential for cognitive and social development. Recent studies have shown that children with autism may be interested in playing with an interactive robot. The robot can engage these children in ways that demonstrate and train essential aspects of human interaction, guiding them in therapeutic sessions to practice more complex forms of interaction found in social human-to-human interactions. This study sets out to investigate Robot-Assisted Autism Therapy (RAAT) and the use of artificial intelligence (AI) approaches for measuring the engagement of children during therapy sessions. The study population consisted of five native Arabic-speaking autistic children aged between 4 and 11 years old. The child-robot interaction was recorded by the robot camera and later used for analysis to detect engagement. The results show that the proposed system offers some accuracy in measuring the engagement of children with ASD. Our findings revealed that robot-assisted therapy is a promising field of application for intelligent social robots, especially to support autistic children in achieving their therapeutic and educational objectives.

Parental Influence in Disengagement during Robot-Assisted Activities: A Case Study of a Parent and Child with Autism Spectrum Disorder

We examined the influence of a parent on robot-assisted activities for a child with Autism Spectrum Disorder. We observed the interactions between a robot and the child wearing a wearable device during free play sessions. The child participated in four sessions with the parent and interacted willingly with the robot, therapist, and parent. The parent intervened when the child did not interact with the robot, considered “disengagement with the robot”. The number and method of intervention were decided solely by the parent. This study adopted video recording for behavioral observations and specifically observed the situations before the disengagement with the robot, the child’s behaviors during disengagement, and the parent’s intervention. The results showed that mostly the child abruptly discontinued the interactions with the robot without being stimulated by the surrounding environment. The second most common reason was being distracted by various devices in the play sessions, such as the wearable device, a video camera, and a laptop. Once he was disengaged with the robot, he primarily exhibited inappropriate and repetitive behaviors accentuating the symptoms of autism spectrum disorder. The child could re-initiate the interaction with the robot with an 80% chance through the parent’s intervention. This suggests that engagement with a robot may differ depending on the parent’s participation. Moreover, we must consider types of parental feedback to re-initiate engagement with a robot to benefit from the therapy adequately. In addition, environmental distractions must be considered, especially when using multiple devices for therapy.

Social Robot Interventions in Mental Health Care and Their Outcomes, Barriers, and Facilitators: Scoping Review

BACKGROUND

The use of social robots as innovative therapeutic tools has been increasingly explored in recent years in an effort to address the growing need for alternative intervention modalities in mental health care.

OBJECTIVE

The aim of this scoping review was to identify and describe social robot interventions in mental health facilities and to highlight their outcomes as well as the barriers and facilitators to their implementation.

METHODS

A scoping review of the literature published since 2015 was conducted using the Arksey and O'Malley's framework. The MEDLINE, Embase, Cochrane Central Register of Controlled Trials, and PsycINFO databases were searched, and 2239 papers were retrieved. The papers included were primary empirical studies published in peer-reviewed literature. Eligible studies were set in mental health facilities and they included participants with a known mental health disorder. The methodological quality of the included papers was also assessed using the Mixed Methods Appraisal Tool.

RESULTS

A total of 30 papers met the eligibility criteria for this review. Studies involved participants with dementia, cognitive impairment, schizophrenia, depression, autism spectrum disorder, attention-deficit hyperactivity disorder, and an intellectual disability. The outcomes studied included engagement, social interaction, emotional state, agitation, behavior, and quality of life.

CONCLUSIONS

The methodological weaknesses of the studies conducted this far and the lack of diversity in the conditions studied limit the generalizability of the results. However, despite the presence of certain barriers to their implementation (eg, technical problems, unsuitable environment, staff resistance), social robot interventions generally show positive effects on patients with mental health disorders. Studies of stronger methodological quality are needed to further understand the benefits and the place of social robots in mental health care.

Gastrointestinal disorders in children with autism: Could artificial intelligence help?

Autism is one of the pervasive neurodevelopmental disorders usually associated with many medical comorbidities. Gastrointestinal (GI) disorders are pervasive in children, with a 46%-84% prevalence rate. Children with Autism have an increased frequency of diarrhea, nausea and/or vomiting, gastroesophageal reflux and/or disease, abdominal pain, chronic flatulence due to various factors as food allergies, gastrointestinal dysmotility, irritable bowel syndrome (IBS), and inflammatory bowel diseases (IBD). These GI disorders have a significant negative impact on both the child and his/her family. Artificial intelligence (AI) could help diagnose and manage Autism by improving children's communication, social, and emotional skills for a long time. AI is an effective method to enhance early detection of GI disorders, including GI bleeding, gastroesophageal reflux disease, Coeliac disease, food allergies, IBS, IBD, and rectal polyps. AI can also help personalize the diet for children with Autism by microbiome modification. It can help to provide modified gluten without initiating an immune response. However, AI has many obstacles in treating digestive diseases, especially in children with Autism. We need to do more studies and adopt specific algorithms for children with Autism. In this article, we will highlight the role of AI in helping children with gastrointestinal disorders, with particular emphasis on children with Autism.