Introduction
An increasing number of children across the globe are being diagnosed with autism spectrum disorder (ASD) (Blaxill
2004; Olds et al.
2013; Scassellati
2005; Wong et al.
2014). From recent studies, a best prevalence estimate of children with ASD of 0.66 % or 1 child in 152 children can be made although also higher numbers have been reported (Volkmar et al.
2014). The Diagnostic and Statistical Manual of Mental Disorders (DSM-V) describes the diagnostic criteria for ASD (American Psychiatric Association
2013). According to the DSM-V, people with ASD often experience persistent problems in social communication and social interaction across multiple contexts on the one hand, and show restricted, repetitive patterns of behaviour, interests, or activities on the other hand. Clinically significant impairments in social, occupational, or other important areas of functioning are apparent (American Psychiatric Association
2013). The symptoms manifest on a continuum, a spectrum, with some individuals showing mild symptoms and others having more severe symptoms and challenges in daily life, and demanding more support (Neurodevelopmental and Group
2012). Together with these differences in severity of symptoms, large variations in symptoms cause ASD to be a highly heterogeneous disorder.
Children with ASD benefit from early and ongoing intervention that is tailored to their specific needs (Volkmar et al.
2014). Even if children reveal progress in some areas during their school time after receiving care, for example in language proficiency, many other areas nevertheless require extensive support, for example in social interaction and communication skills (Volkmar et al.
2014). Most children with ASD continue to have ASD as an adult and continue to experience challenges related to independent living, employment, social relationships and mental health (Myers and Johnson
2007).
Ongoing research has proven the acceptance and efficiency of technology as a support tool for the therapy and education of individuals with ASD and the people who support them on a daily basis (Aresti-Bartolome and Garcia-Zapirain
2014; Boucenna et al.
2014; Goldsmith and LeBlanc
2004; Grynszpan et al.
2014; Lee and Hyun
2015).
Theory of Mind (ToM) refers to the ability to understand one’s own and other people’s beliefs, intentions, desires, imagination, and emotions (Baron-Cohen et al.
1985). Often children with autism have difficulties in ToM. Technologies might provide tools to address these impairments because they can create situations or environments in which children can practice and learn in a safer (e.g. more predictable) and more pleasant manner than when they would practice this (only) with a person. Technologies can deliberately focus on targeting the strengths and weaknesses of the disorder by creating controlled environments that might reduce the anxiety that “real” social situations may cause for children with ASD (Aresti-Bartolome and Garcia-Zapirain
2014). More specifically, socially interactive robots or robot assisted therapy are suggested to be of potential added value in the therapy of children with autism (Cabibihan et al.
2013). Boucenna et al. (
2014) suggest a number of reasons for this expected beneficial effect; it might be easier for children with ASD to interact with robots than with humans. Robots (less complex, more predictable, and simpler) can also provide novel sensory stimuli and tend to occupy a special niche between inanimate toys (which do not trigger novel social behaviours for these children) and humans (which can be a source of confusion or even distress for them) (Scassellati et al.
2012). In other words, robots enable embodied interactions that are appealing for children with ASD. Possibly robots can simultaneously provide human-like social cues (e.g. waving, smiling) while maintaining object-like simplicity (e.g. in a consistent manner, limited facial expressions) (Thill et al.
2013). Thill et al. (
2013) summarized a number of advantages of using robots for children with ASD: robots can be applied in a controlled manner so that only relevant information is presented minimising the risk of creating stressful and complex situations, robots are better in endless repetition than people, and variations can be made in a conscious (and safe) manner.
Scassellati et al. (
2012) report encouraging effects such as increased engagement, increased levels of attention and novel social behaviours, for example joint attention and imitation, when the children interact with robots.
Earlier work (Cabibihan et al.
2013) presented a compilation of robots that have been studied for children with autism and distinguished a number of benefits and roles that robots could have. These roles range from a “friendly playmate”, a “behaviour eliciting agent”, a “social mediator” or a “social actor” to a “personal therapist” (Diehl et al.
2012). A review of the clinical use of robots for individuals with ASDs identified four categories for the roles for interactive robots in clinical applications: the response of individuals (often children) with ASD to robots or robot-like behaviour in comparison to human behaviour, the use of robots to elicit behaviours, the use of robots to model, teach or practice a skill and the use of robots to provide feedback on performance (Aresti-Bartolome and Garcia-Zapirain
2014).
Although most of these studies yielded positive effects using robots for children with autism (e.g. show an increase in desired target behaviours, increased response times, show appreciation/interest for robot interaction), not all children would benefit from (the same) robotic support (Diehl et al.
2012) or would perform better with a human counterpart compared with a robot (Duquette et al.
2008). Mixed results and variability in the nature of the affective response (e.g. positive or negative reaction towards the robot) are also reported; children are not likely to always react positively to the robot (Feil-Seifer and Mataric
2011). This, again, underlines the need for personalised and tailored interventions for this heterogeneous target group.
With respect to teachers’ acceptance on the use of robots in education, one study found that pre-school and elementary teachers accepted a human-like robot to serve as an interactive tool in the teaching process (Fridin and Belokopytov
2014). Other findings regarding attitudes towards the use of robots in (psycho)therapy or education for children show that people, overall, tend to have positive attitudes, considering them as useful and potentially effective tools in psychological treatments or interventions (Costescu and David
2014; Fridin and Belokopytov
2014; Oros et al.
2014).
Despite this work with promising results, the actual current state of application of robots for children with autism in care/therapy and education practices is still relatively in an early stage. More research is needed to understand the actual clinical effects and added value in therapy and education (Diehl et al.
2012). Moreover, it would be interesting to better understand in what areas robots can actually add value to the functioning of children with autism, and how this relates to the “International Classification of Functioning, Disability and Health” (ICF) (World Health Organization
2007). The ICF for children and youth (ICF-CY) provides a classification for health and health-related domains and addresses all aspects of functioning specifically for children and youth.
A critical review by Diehl et al. (
2012) concluded that many of these studies are explorative in nature and have methodological limitations and do not necessarily focus on the clinical application of the technology but more on the development of the technology (Diehl et al.
2012). The exploration of robot-based autism intervention has often been directed at clinical or therapy settings and less on educational settings in which children might also benefit from the use of robots in the curriculum (Shamsuddin et al.
2015).
Furthermore, although research has proved the potential added value of different kinds of technologies for children with autism, however, often these tools currently lack the ability to personalise to a specific person’s needs (American Psychiatric Association
2013). Especially for such a diverse and heterogeneous target group as children with autism, it is extremely important that interventions address challenges in different dimensions and a personalised offering is possible (Volkmar et al.
2014). Technologies, including robots might be able to fulfil this requirement as they allow for personalisation and customisation to the individual’s specific needs.
Actual clinical application of robot technology in practice requires the expertise of both technology developers as well as experts in the area of children with ASD. Although public opinion and press devote more and more attention to the use of robots in the therapy or education for children with ASD, scientific peer reviewed publications of systematic clinical effectiveness of the actual implementation of robot based interventions for children with ASD are still scarce.
For robots to be of clinical added value, obviously, teachers and/or care professionals have to accept, adopt and embed these robots in their daily practices. To be used, interventions need to meet the needs of children as well as the needs and practices of these professionals. This is a rather challenging task. For robot developers, it can be quite hard to understand and relate to the needs of this heterogeneous target group and therefore difficult to develop appropriate robot systems to be used as part of interventions. For professionals working with children with ASD on the other hand, the world of social robots seems quite invisible, far away or unreachable. Yet, in order for robot assisted therapy to bring added value to the lives of children with ASD and their carers, connecting professionals from the robotic community with experts in the area of ASD makes a lot of sense.
This study aims to contribute to this by providing a systematic overview of objectives that are important for children with autism and to provide a mapping of available robots to these objectives. This may facilitate the awareness and creation of common understanding between robot developers and ASD professionals (both educators at (special) schools or therapists working in care settings) who are (intending to become) active in the area of robot assisted therapy for children with autism. For ASD professionals it may provide an overview of robots that are currently presented in peer reviewed literature. For the robotic developers on the other hand, it may give insight into relevant ASD domains and objectives that professionals in the field are actually working on.
In short, this research entailed two main goals:
1.
To create an overview of relevant therapy and educational objectives that professionals are actually working on in practice for children with ASD.
2.
To identify robots focusing on children with ASD that are presented in peer reviewed articles and to relate them to the overview of objectives.
Discussion
The main results of this research indicate that professionals work on a broad variety of therapy and/or educational objectives in a wide range of domains for children with ASD and that state of the art robots focuses on only a small set of these objectives.
The wide range of therapy and educational objectives for children with autism, resulting from the focus groups, is in line with the heterogeneous nature of the disorder (American Psychiatric Association
2013). Professionals indicated that they are focused and driven by supporting these children in coping with their ASD in daily life towards independent living rather than trying to “fix” their impairments, challenges or differences. These objectives could be categorised into 9 domains and 74 objectives.
Best matching ICF-CY codes were collected for each objective (World Health Organization
2007). Since the ICF-CY offers an universal standardised categorisation, it is not specifically constructed for children with ASD. Therefore, in some cases it was challenging to find the best matching ICF-CY code to the objectives, so it was ensured that this task was done with utmost care and attention of multiple project members who were actively involved in the sessions with the professionals.
The participants of the focus group sessions are all highly specialised experts in the area of education or therapy for children with ASD. In the Netherlands many children with ASD attend special schools where they receive special education and dedicated therapy at school. This implies that these professionals are highly specialised in autism, and that the groups of children at schools are rather small (maximum 7–12 children in a classroom) and mostly existing of children with autism. This might be different in other countries and is also changing in the Netherlands (more children with autism will be integrated in regular education).
The results of the literature study, on identifying state of the art robots for this target group, showed that at this moment in time a relatively small subset (n = 24) of this ASD objectives (n = 74) is addressed by the identified robots (n = 14), leaving quite a large number of ASD objectives unmet by robotic support.
Most of the reported studies in this work used a tele-operated Wizard of Oz style in which a person operates the behaviour of the robot. This creates a benefit of flexibility for the human who can sensitively read the social situation and the child and accordingly control the robot to act appropriately. At the same time this also creates a burden (increase of workload) on that person and often extra technical personnel is required to smoothly operate the robot. This is in line with other work stating that few of the current approaches (in robot assisted therapy for children with ASD) use autonomously interactive robots (Thill et al.
2013). Thill et al. (
2013) actually call for a need for more autonomous therapeutic robots rather than remote controlled robots.
For a detailed insight into the effects of the robots and types of the studies identified in Table
1, we refer to earlier reviews on the use of robots in the context of ASD (Cabibihan et al.
2013; Diehl et al.
2012). When focusing on the domains, we conclude that the majority of the robot studies were related to 3 of the 9 domains; “Social/Interpersonal interactions and relations”, “Play” and “Communication”. Other domains such as “Self-care, independent living”, “Pre-school skills”, “Emotional wellbeing”, and “Functioning in daily reality” were (largely) unaddressed by the identified robot studies. This is not a surprising result since the main challenges of children with ASD are indeed related to social and communicative challenges as well as impairments in play behaviours (American Psychiatric Association
2013). Typical ASD objectives in these domains, such as imitation, collaborative play, (joint) attention, as well as turn taking behaviour, were often targeted by (quite similar) robotic support in studies. These rather typical ASD objectives are primary difficulties that children with autism experience that in turn create challenges in different areas of their daily living as can be seen in the overview (for example “follow up instructions”). Robotic solutions can possibly also be of surplus value in other (more indirect) areas as well.
When mapping the robotic studies to the objectives overview, we aimed to find the objective in the overview that matches the focus of specific study best.
The overview can function as creating awareness of the scope of objectives for children with autism that professionals are actually working on with children with ASD. The intention is not to suggest to use a robot for all objectives for all children. Developing meaningful robot assisted therapy requires a profound understanding of the target group. To better understand the possibilities and impossibilities, appropriateness or inappropriateness of robotic support in the objectives and domains, more research is needed. For example, using robots to learn children to follow up instructions might be more appropriate than using robots to teach them to negotiate about rules. Moreover, professionals might express a stronger need for additional interventions targeting some objectives rather than others. And some children might react better to interventions using robots than others.
The next step would be that these objectives will be specified and translated into possible robotic interventions that matches the user requirements of both the children and professionals.
As indicated before, especially the diverse and heterogeneous nature of the ASD calls for a high degree of tuning/adaptation/personalisation or individualisation in the interventions. It asks for a bottom-up, client centred, tailor made approach. Robotic interventions might be very well capable of addressing this need due to their many potential advantages, however, current state of the art robots for children with ASD has probably not reached its full potential yet in terms of interventions/clinical application. Furthermore, most of these studies (still) present the robots [operated by a (technical) researcher] as a platform focusing on robot-child interactions rather than a robot assisted intervention in the hands of the care professional embedded into care protocols and actual therapy/educational settings. This is in line with conclusions of earlier work (Bekele et al.
2014; Diehl et al.
2012). This also corresponds with a meta-analysis done on innovative technology based interventions that concluded that no evidence based robot interventions are currently available for children with ASD (Grynszpan et al.
2014). Robot assisted interventions can be seen as a therapy or education tool in the hands of the professionals. In order to be used, these robots do not only have to address the needs of the children with ASD, but they also have to be sensitive to the requirements posed by the professionals. Making it work/happen in practice requires more than the stability and availability of a meaningful robot. If the robot is not incorporated in the care or education provision and application of interventions no child nor professional will ever benefit from robots. In order to do so, we need to better understand the professionals requirements for robot assisted interventions. It is crucial to investigate how robot-based (interaction) scenarios can be integrated into existing therapy/education environments for children with autism (Shamsuddin et al.
2015). Taking this work to the next level implies moving beyond focusing solely on the robot towards embedding a robot in a clinical intervention or therapy/education protocol. For this, more applied research in an education/therapeutic context (e.g. in a school or care setting) is required to understand better what is needed in terms or intervention/education requirements from ASD professionals, the envisioned end-users of robot assisted therapy.
Research has proven the efficacy of many technologies for people with autism. However, although these tools are useful, often these are rather general in nature, resulting in a lack of personalisation to a person’s specific needs (American Psychiatric Association
2013). It is crucial to design appropriate interventions that can be tailored to the individual needs of this target group in order to increase people’s independence and productive functioning (Volkmar et al.
2014).
Technology becomes more and more part of everyday life and activities, and it is inevitable that technology will be integrated into autism intervention as well (McCleery
2015). However, in order to specify and develop meaningful robot based interventions, it is crucial that professionals, stakeholders as well as technology developers co-create (McCleery
2015). This research aimed to provide a the base for understanding relevant objectives in the therapy and/or education of children with ASD, which is a necessary first step in user centred design process for developing robot assisted interventions. In conclusion, this work is expected to be valuable for experts in the area of children with ASD who are considering using robots as innovative tools in education or therapy. Simultaneously, it is considered to be useful for robot developers who are interested in application domains and are in need of a better understanding of the needs of the target group of children with autism.
It may contribute to the creation of common understanding between ASD professionals and robot developers in their (joined) mission to create meaningful robot interventions for children with autism in the quest to support these children to become the best possible version of themselves in life.