Are social robots ready yet to be used in care and therapy of autism spectrum disorder: A systematic review of randomized controlled trials

Do Children with Autism Spectrum Disorders Show Selective Trust in Social Robots?

PURPOSE

Previous researches suggest that social robots can facilitate the learning of children with Autism Spectrum Disorder (ASD) by enhancing their interests, engagement, and attention. However, there is limited understanding regarding whether children with ASD can learn directly from the testimony of social robots and whether they can remain vigilant based on the perceived accuracy of these robots. Therefore, the present study was conducted to examine whether children with ASD demonstrated selective trust towards social robots.

METHODS

Twenty-nine children with ASD between ages of 4-7 years, and 38 typically-developing (TD) age and IQ-matched peers participated in classic selective trust tasks. During the tasks, they learned the names of novel objects from either a pair of social robots or a pair of human informants, where one informant had previously been established as accurate and the other inaccurate.

RESULTS

Children with ASD trusted information from an accurate social robot over an inaccurate one, similar to their performance with human informants. However, compared to TD children, children with ASD exhibited lower levels of selective trust regardless of the type of informants they learned from.

CONCLUSIONS

Our study suggests that children with ASD can selectively trust and acquire knowledge from social robots, shedding light on the potential use of social robots in supporting individuals with ASD.

Effectiveness of a Robot-Assisted Psychological Intervention for Children with Autism Spectrum Disorder

Difficulties with social interaction characterise children with Autism Spectrum Disorders and have a negative impact in their everyday life. Integrating a social-humanoid robot within the standard clinical treatment has been proven promising. The main aim of this randomised controlled study was to evaluate the effectiveness of a robot-assisted psychosocial intervention and the secondary aim was to investigate potential differences between a robot-assisted intervention group and a control group receiving intervention by humans only. The analysis of the results showed that robot-assisted intervention could be beneficial by improving children's psychosocial skills. This improvement was highlighted by neuropsychological testing and parent reporting. Group comparison only presented minimal statistically significant differences. The study underpins the potential of robot-assisted interventions to augment standard care.

Immersive robotic telepresence system to support a person with intellectual and motor disabilities perform a daily task: a case study

Purpose

In this proof-of-concept study, the authors assessed the feasibility of using a humanoid robot controlled remotely via an immersive telepresence system to support a person with intellectual and motor disabilities performing a daily task (i.e. setting a table for lunch).

Design/methodology/approach

The system involved a head-mounted display and two joysticks. A teleoperator was able to see through the video cameras of the robot and deliver the instructions verbally to the participant located in a different room. To assess the system, a baseline phase (A) was followed by an intervention (i.e. tele-operated support) phase (B) and a return to a baseline phase (A).

Findings

Data showed a marked increase in the average frequency of task steps correctly performed from baseline (M = 15%) to intervention (M = 93%). Accuracy reached 100% in the return to baseline.

Originality/value

These preliminary findings, along with qualitative feedback from users, suggest that an immersive telepresence system may be used to provide remote support to people with intellectual and motor disabilities.

The use of social robots with children and young people on the autism spectrum: A systematic review and meta-analysis

BACKGROUND

Robot-mediated interventions show promise in supporting the development of children on the autism spectrum.

OBJECTIVES

In this systematic review and meta-analysis, we summarize key features of available evidence on robot-interventions for children and young people on the autism spectrum aged up to 18 years old, as well as consider their efficacy for specific domains of learning.

DATA SOURCES

PubMed, Scopus, EBSCOhost, Google Scholar, Cochrane Library, ACM Digital Library, and IEEE Xplore. Grey literature was also searched using PsycExtra, OpenGrey, British Library EThOS, and the British Library Catalogue. Databases were searched from inception until April (6th) 2021.

SYNTHESIS METHODS

Searches undertaken across seven databases yielded 2145 articles. Forty studies met our review inclusion criteria of which 17 were randomized control trials. The methodological quality of studies was conducted with the Quality Assessment Tool for Quantitative Studies. A narrative synthesis summarised the findings. A meta-analysis was conducted with 12 RCTs.

RESULTS

Most interventions used humanoid (67%) robotic platforms, were predominantly based in clinics (37%) followed home, schools and laboratory (17% respectively) environments and targeted at improving social and communication skills (77%). Focusing on the most common outcomes, a random effects meta-analysis of RCTs showed that robot-mediated interventions significantly improved social functioning (g = 0.35 [95%CI 0.09 to 0.61; k = 7). By contrast, robots did not improve emotional (g = 0.63 [95%CI -1.43 to 2.69]; k = 2) or motor outcomes (g = -0.10 [95%CI -1.08 to 0.89]; k = 3), but the numbers of trials were very small. Meta-regression revealed that age accounted for almost one-third of the variance in effect sizes, with greater benefits being found in younger children.

CONCLUSIONS

Overall, our findings support the use of robot-mediated interventions for autistic children and youth, and we propose several recommendations for future research to aid learning and enhance implementation in everyday settings.

PROSPERO REGISTRATION

Our methods were preregistered in the PROSPERO database (CRD42019148981).

A Trustworthy Robot Buddy for Primary School Children

Social robots hold potential for supporting children’s well-being in classrooms. However, it is unclear which robot features add to a trustworthy relationship between a child and a robot and whether social robots are just as able to reduce stress as traditional interventions, such as listening to classical music. We set up two experiments wherein children interacted with a robot in a real-life school environment. Our main results show that regardless of the robotic features tested (intonation, male/female voice, and humor) most children tend to trust a robot during their first interaction. Adding humor to the robots’ dialogue seems to have a negative impact on children’s trust, especially for girls and children without prior experience with robots. In comparing a classical music session with a social robot interaction, we found no significant differences. Both interventions were able to lower the stress levels of children, however, not significantly. Our results show the potential for robots to build trustworthy interactions with children and to lower children’s stress levels. Considering these results, we believe that social robots provide a new tool for children to make their feelings explicit, thereby enabling children to share negative experiences (such as bullying) which would otherwise stay unnoticed.

Android Robot Promotes Disclosure of Negative Narratives by Individuals With Autism Spectrum Disorders

Many individuals with autism spectrum disorders (ASD) demonstrate some challenges with personal narrative writing. Sentence completion tests (SCT) is a class of semi-structured projective techniques and encourage respondents to disclose their private narratives. Even in SCT, only providing beginning of sentences is inadequate to compensate atypicalities in their creativity and imagination, and self-disclosure is difficult for many individuals with ASD. It is reported that many individuals with ASD often achieve a higher degree of task engagement through interactions with robots and that robotic systems may be useful in eliciting and promoting social communication such as self-disclosure for some individuals with ASD. There is a possibility that exemplification by android robots in place of human interviewers can result in a higher degree of task engagement for individuals with ASD. The objective of this study was to investigate whether additional exemplifications by android robots in the SCT can prompt self-disclosure for individuals with ASD. We compared the difference in disclosure statements and subjective emotion in the testing paper of the SCT in additional exemplification by an android robot and a human interviewer. In addition, we assessed the disclosure statements and subjective emotions in the SCT, for which exemplifications were written on testing paper to make the comparison. Our quantitative data suggested that exemplification by android robot promoted more self-disclosure, especially about the negative topic compared to exemplification by a human interviewer and that written on test paper. In addition, the level of participant embarrassment in response to exemplification by the android robot seemed to be lower compared to that in the human interviewer condition. In the assessment and support for individuals with ASD, eliciting self-disclosure is a pressing issue. It is hoped that the appropriate use of robots will lead to a better understanding and support for their application.

Differences in the Optimal Motion of Android Robots for the Ease of Communications Among Individuals With Autism Spectrum Disorders

Android robots are employed in various fields. Many individuals with autism spectrum disorders (ASD) have the motivation and aptitude for using such robots. Interactions with these robots are structured to resemble social situations in which certain social behaviors can occur and to simulate daily life. Considering that individuals with ASD have strong likes and dislikes, ensuring not only the optimal appearance but also the optimal motion of robots is important to achieve smooth interaction and to draw out the potential of robotic interventions. We investigated whether individuals with ASD found it easier to talk to an android robot with little motion (i.e., only opening and closing its mouth during speech) or an android robot with much motion (i.e., in addition to opening and closing its mouth during speech, moving its eyes from side to side and up and down, blinking, deeply breathing, and turning or moving its head or body at random). This was a crossover study in which a total of 25 participants with ASD experienced mock interviews conducted by an android robot with much spontaneous facial and bodily motion and an android robot with little motion. We compared demographic data between participants who answered that the android robot with much motion was easier to talk to than android robot with little motion and those who answered the opposite. In addition, we investigated how each type of demographic data was related to participants' feeling of comfort in an interview setting with an android robot. Fourteen participants indicated that the android robot with little motion was easier to talk to than the robot with much motion, whereas 11 participants answered the opposite. There were significant differences between these two groups in the sensory sensitivity score, which reflects the tendency to show a low neurological threshold. In addition, we found correlations between the sensation seeking score, which reflects the tendency to show a high neurological threshold, and self-report ratings of comfort in each condition. These results provide preliminary support for the importance of setting the motion of an android robot considering the sensory traits of ASD.