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More Attention and less repetitive behaviors using a robot with children with autism
Abstract
The aim of the present study was to assess the usefulness of QTrobot, a socially assistive robot, in interventions with children with autism spectrum disorder (ASD) by assessing children's attention, imitation, and presence of repetitive and stereotyped behaviors. Fifteen children diagnosed with ASD, aged from 4 to 14 years participated in two short interactions, one with a person and one with the robot. Statistical analyses revealed that children directed more attention towards the robot than towards the person, imitated the robot as much as the person, and engaged in fewer repetitive or stereotyped behaviors with the robot than with the person. These results support previous research demonstrating the usefulness of robots in short interactions with children with ASD and provide new evidence to the usefulness of robots in reducing repetitive and stereotyped behaviors in children with ASD, which can affect children's learning.
... The environment of their interaction with the robot is more controlled and predictable than that with the human, and individuals with ASD can feel safe, and become less frustrated when interacting with robots (Feil-Seifer & Matarić, 2009;Sartorato et al., Research, Society andDevelopment, v. 10, n. 11, e564101120269, 2021 (CC BY 4.0) | ISSN 2525-3409 | DOI: http://dx.doi.org/10.33448/rsd-v10i11.20269 3 2017). The simplicity of robots and their ability to repeat patterns in a foreseeable way correspond to the characteristics of children with ASD, who seek sameness and who, themselves, manifest repetitive behaviors (Costa et al., 2018). It has been observed that children with ASD show better results in terms of the desired target behavior when interacting with a robot than in virtual learning environments. ...
... In the study of Taheri et al. (2018), the participants were a pair of high-and low-functioning fraternal twins (Taheri et al., 2018). IQ scores were reported in four of the ten studies (Costa et al., 2018;Ismail et al., 2012;Shamsuddin et al., 2012;Shamsuddin et al., 2013). The characteristics of the participants in the studies reviewed here are presented in Table 2. ...
... The ten studies included in the review took place in six countries on three continents. Three studies were carried out in Malaysia Shamsuddin et al., 2012;Shamsuddin et al., 2013), two in the USA (Srinivasan et al., 2015;Stanton et al., 2008) and Iran (Taheri et al., 2018;Taheri et al., 2021) and one in Canada (Duquette et al., 2008), Luxemburg (Costa et al., 2018) and Romania (David et al., 2020). The distribution indicates the worldwide research interest in studying the effect of REIs on RSBs in children with ASD. ...
Repetitive and stereotyped behaviors (RSBs) are core symptoms of Autism Spectrum Disorder (ASD), and they affect the functionality of individuals with ASD. Robot assisted therapy can be beneficial for children with ASD in various ways, but relevant research focusing specifically on robot enhanced interventions (REIs) for RSBs in children with ASD has been limited. A scoping review was conducted to explore the role of REIs on RSBs of children with ASD and to investigate the components of REIs focusing on RSBs of younger and older children with ASD. A literature search was made in the databases of Scopus, PubMed, Web of Science, EBSCO, MEDLINE, and Google Scholar, using keywords pertaining to robots, ASD, RSBs, and children.Of the 89 studies identified, 10 met the inclusion criteria. They involved 99 participants aged 3-14 years (mean 7.27 years) from six countries on three different continents. These studies varied with respect to sample size, the research design, the robot used, the length of intervention, the training and the type of measurement. Following the application of most REIs, the participants showed reduction in RSBs. Only one study reported that REI led to some increase in stereotyped behaviors in children with ASD and one detected no training-related changes in repetitive behaviors.The review findings indicate the potential of REIs for reducing RSBs in children with ASD, but the relevant studies were diverse, and controlled studies with larger samples of children and rigorous design are needed to clarify their impact.
... This includes fostering joint attention skills, provide feedback on mathematical activities, and support the monitoring process for acquiring metacognitive skills (Maras, Gamble, & Brosnan, 2019;Warren et al., 2015). As a final point, current research on the use of Artificial Intelligence is exploring the adoption of AI-powered robots to teach skills useful for social interaction, both in rehabilitative and educational contexts (Costa et al., 2018;Kim et al., 2017;Warren et al., 2015;Zhang et al., 2022). Even in these circumstances, through sophisticated algorithms and data-based analyses, AI models may identify student's learning style, strengths, and weaknesses through interaction, allowing for personalized learning paths that adapt in real-time (Costa et al., 2018;Kim et al., 2017;Ramdoss et al., 2012 a, b). ...
... As a final point, current research on the use of Artificial Intelligence is exploring the adoption of AI-powered robots to teach skills useful for social interaction, both in rehabilitative and educational contexts (Costa et al., 2018;Kim et al., 2017;Warren et al., 2015;Zhang et al., 2022). Even in these circumstances, through sophisticated algorithms and data-based analyses, AI models may identify student's learning style, strengths, and weaknesses through interaction, allowing for personalized learning paths that adapt in real-time (Costa et al., 2018;Kim et al., 2017;Ramdoss et al., 2012 a, b). ...
With the rise of educational technologies that use Artificial Intelligence (AI), this study explores future learning support teachers' acceptance and intention to use them in classrooms with students with Autism Spectrum Disorder (ASD). Research indicates that educational technology may significantly enhance learning for children with ASD in several developmental areas. However, integrating such technologies in schools remains under researched regarding teachers' intentions to integrate such technologies in classrooms with ASD students. For that reason, this study aims to investigate it using the Unified Theory of Acceptance and Use of Technology as the theoretical framework. A questionnaire was administered to future learning support teachers enrolled at the eighth cycle of the Specialization course for those wishing to acquire the Learning support teacher's warrant to work in upper secondary schools. The findings reveal a positive predisposition towards the adoption of AI and technologies, particularly emphasizing the importance of AI knowledge as a factor related to the willingness to employ it in educational contexts. Additionally, intrinsic value, the enjoyment and reward derived from using technology, emerged as a significant factor impacting teachers' intentions to integrate AI and educational technologies in their classrooms.
... Para Sartorato et al., (2017), las actividades estructuradas que se diseñan con los robots proporcionan un refuerzo positivo mediante luces, sonidos o movimiento de las partes del cuerpo que posibilitan que el niño reciba información sobre las mejoras en las diversas habilidades entrenadas. Además, la posibilidad de que el robot desarrolle patrones repetitivos facilita que el alumnado pueda aprender de manera más sencilla su respuesta ante una determinada situación social (Costa et al., 2018). A pesar de ello, el uso del robot no tiene como finalidad remplazar la interacción humanohumano, sino que debe actuar como un mediador entre el niño con TEA y los otros humanos . ...
... El hallazgo puede deberse a que los niños con la imitación están realizando actividades de repetición, que se adecua a los intereses del autista (Snow et al., 1987). En esta línea, la posibilidad que tienen los robots de desarrollar patrones repetitivos facilita que el alumnado pueda aprender de manera sencilla y satisfactoria (Costa et al., 2018). Asimismo, los robots generan refuerzos positivos mediante luces, sonidos o movimientos del cuerpo, lo que puede generar que el niño tenga una mayor atención y exprese un sentimiento de felicidad al participar en la actividad (Sartorato et al., 2017). ...
Actualmente, la tecnología es la herramienta más utilizada en el desarrollo de las actividades de la vida diaria. Cada vez es mayor, el número de campos de conocimiento que se benefician de su versatilidad y la aplicación en el desarrollo de sus actividades. En el entorno educativo, permite generar actividades adaptadas a las necesidades del alumnado. En los últimos años, la robótica y la inteligencia artificial son las que mayor difusión están teniendo. Las características de estas herramientas favorecen su aplicación con el alumnado con Trastorno del Espectro Autista. Por tanto, el objetivo de la investigación es la aplicación de la robótica para favorecer la comunicación e interacción social en el alumnado con autismo analizando las emociones que manifiestan a lo largo de las distintas actividades. Para ello, se implementó un estudio piloto con el robot NAO y cuatro niños autistas que desarrollaron actividades de imitación, juego e interacción social. Durante su realización se utilizó un sistema automático basado en redes neuronales convolucionales para detectar los estados de ánimo en el proceso de interacción. Los resultados muestran que tristeza, felicidad y enfado son las emociones que tiene una mayor probabilidad de producirse en los participantes. Por tanto, se concluye que el robot y el sistema de inteligencia artificial son un elemento fundamental para ayudar a expresar sus emociones en las interacciones sociales.
... After, we divided the five studies according to their ICF criteria in order to reduce their heterogeneity. For the analysis of the (Yun et al., 2017;Ali et al., 2019;Chung, 2019) (So et al., 2019a;Costa et al., 2018;Ahmad et al., 2017) EEG for attentiveness Ali et al., 2019) Fixation time (Yoshikawa et al., 2019;Wan et al., 2019) (Ahmad et al., 2017) Gaze transitions Taheri et al., 2018;Aryania et al., 2020) Correct gazing (Javed et al., 2019;Billing et al., 2020;Sperati et al., 2020) (Javed et al., 2020) Attention Head movement (Del Coco et al., 2018;Zheng et al., 2016;Billing et al., 2020) (Jain et al., 2020) Number of trials to hit target (Zheng et al., , 2020 Number of prompts Nie et al., 2018;Zheng et al., 2020) Time between cue and child response (Ramírez-Duque et al., 2020) Early Social Communication Scale (Carlson et al., 2018;Nie et al., 2018;So et al., 2020) Motor Number of times of complete imitation Imitation accuracy (Costa et al., 2018;Javed et al., 2018;Taheri et al., 2018 Number of prompts to follow the robot (Petric et al., 2017;Beer et al., 2016) (imitation/ Time differences between robot's movement and child movement (Aryania et al., 2020) gestures) Recognition of gestures (So et al., 2018a(So et al., , 2019b Dynamic time warping costs between gestures done (Wijayasinghe et al., 2016) Ranking in emotion recognition tasks (Bharatharaj et al., 2017c;Chevalier et al., 2017aChevalier et al., ) (alvador et al., 2016 Emotional Test of Emotion Comprehension (Marino et al., 2020) Expression Emotional Lexicon test (Marino et al., 2020) Recognition Heart rate (Giannopulu et al., 2018;Yun et al., 2016;Giannopulu et al., 2020) Heart rate variability (Silva et al., 2019) Emotional feeling report (Giannopulu et al., 2018;Yun et al., 2016;Giannopulu et al., 2020) treatment effects, we used the standardised mean difference with 95% confidence interval. ...
... After, we divided the five studies according to their ICF criteria in order to reduce their heterogeneity. For the analysis of the (Yun et al., 2017;Ali et al., 2019;Chung, 2019) (So et al., 2019a;Costa et al., 2018;Ahmad et al., 2017) EEG for attentiveness Ali et al., 2019) Fixation time (Yoshikawa et al., 2019;Wan et al., 2019) (Ahmad et al., 2017) Gaze transitions Taheri et al., 2018;Aryania et al., 2020) Correct gazing (Javed et al., 2019;Billing et al., 2020;Sperati et al., 2020) (Javed et al., 2020) Attention Head movement (Del Coco et al., 2018;Zheng et al., 2016;Billing et al., 2020) (Jain et al., 2020) Number of trials to hit target (Zheng et al., , 2020 Number of prompts Nie et al., 2018;Zheng et al., 2020) Time between cue and child response (Ramírez-Duque et al., 2020) Early Social Communication Scale (Carlson et al., 2018;Nie et al., 2018;So et al., 2020) Motor Number of times of complete imitation Imitation accuracy (Costa et al., 2018;Javed et al., 2018;Taheri et al., 2018 Number of prompts to follow the robot (Petric et al., 2017;Beer et al., 2016) (imitation/ Time differences between robot's movement and child movement (Aryania et al., 2020) gestures) Recognition of gestures (So et al., 2018a(So et al., , 2019b Dynamic time warping costs between gestures done (Wijayasinghe et al., 2016) Ranking in emotion recognition tasks (Bharatharaj et al., 2017c;Chevalier et al., 2017aChevalier et al., ) (alvador et al., 2016 Emotional Test of Emotion Comprehension (Marino et al., 2020) Expression Emotional Lexicon test (Marino et al., 2020) Recognition Heart rate (Giannopulu et al., 2018;Yun et al., 2016;Giannopulu et al., 2020) Heart rate variability (Silva et al., 2019) Emotional feeling report (Giannopulu et al., 2018;Yun et al., 2016;Giannopulu et al., 2020) treatment effects, we used the standardised mean difference with 95% confidence interval. ...
Robotic therapies are receiving growing interest in the autism field, especially for the improvement of social skills of children, enhancing traditional human interventions. In this work, we conduct a scoping review of the literature in robotics for autism, providing the largest review on this field from the last five years. Our work underlines the need to better characterize participants and to increase the sample size. It is also important to develop homogeneous training protocols to analyse and compare the results. Nevertheless, 7 out of the 10 Randomized control trials reported a significant impact of robotic therapy. Overall, robot autonomy, adaptability and personalization as well as more standardized outcome measures were pointed as the most critical issues to address in future research.
... Having documented the promise of leveraging VUIs' ability to strengthen children's language development, application developers have increasingly created voice-based apps targeted at children's use. These apps have increasingly been developed as learning to engage in dialogue with children based on pre-designed dialogical flows and focused on activities with interactive speech-based content [7]. However, these designs are not without challenges. ...
... Therefore, VUI design must naturally target the population it aims to serve because children's interactions with VUI influence their current actions and thoughts but have effects on how they will intermingle with other people in the future [13]. As a result of the escalating market demand for VUIs on the international market to support young children's language development, developers have created thousands of such VUI applications available to children [7]. These applications engage in conversation with children based on pre-designed dialogical flows and communicate with children via specific activities with collaborative speechbased content [14]. ...
Voice User Interface (VUI) is an Artificial Intelligence tool that enables children to access a computing device and complete tasks through speech instead of using learning methods. VUI, a form of AI (Artificial Intelligence), takes a sound that children articulate in a spoken statement and use intent recognition to understand the action required to fulfill the child’s spoken request. The design and features of VUI have been developed to increase the interpersonal level of communication with users and, to some degree, make voice assistants behave like humans. The features that have been created, have been shaped in such a way as to improve learning efficacy and ease of use for early childhood learning development. The current available VUIs in the market have been geared to provide children with a simpler way to interact with access to educational technology learning tools. The research posits that there are two primary uses of VUI in childhood learning development exploration, whereby children use VUI as a form of entertainment and information seeking, and children use VUI to develop various knowledge facets. For children in the early language stages currently using language to communicate, VUI language stimulation can help children to engage in continuous communication processes, use and understand various words, and successfully complete more complex sentences. The research seeks to state the problems associated with VUI and the standard opinions based on research associated with the problem. Moreover, the study seeks to articulate the hypothesis that VUI is an effective tool for early childhood language learning through the use of peer-reviewed evidence and examples, to the hypothesis, to generate new and innovative perspectives.
... Children with ASD manifest repetitive behaviors and are looking for consistency. These features are addressed in the ability of robots to replicate specific patterns predictably, thus supporting the successful engagement of children with ASD in the process (Costa et al. 2018), and encouraging the reduction of their challenging behaviors (Costa et al. 2018, Ismail et al. 2012. ...
... Children with ASD manifest repetitive behaviors and are looking for consistency. These features are addressed in the ability of robots to replicate specific patterns predictably, thus supporting the successful engagement of children with ASD in the process (Costa et al. 2018), and encouraging the reduction of their challenging behaviors (Costa et al. 2018, Ismail et al. 2012. ...
Children with autism spectrum disorder (ASD) show great interest in technological devices, and especially in robots. Several studies in the field have suggested that socially assistive robotics (SARs) can help children with ASD in the enhancement of their social skills and communication, and in the reduction of their stereotypical behaviors. Few published research results are available regarding robot programming or coding in the context of STEM education (Science, Technology, Engineering and Mathematics) for these children. In this pilot study, the authors designed and implemented educational activities with the robot “Codey Rocky”, a ready-to-use robot designed for code learning and programming by primary school children. In this pilot study, the participation of two eight-year-old schoolchildren, a girl with ASD and intellectual deficit (ID) and a boy of typical development (TD) in triadic interactions with the robot, led to the enhancement of the social and communication skills of the girl with ASD. A decrease in her challenging behaviors was also observed although she manifested repetitive and stereotyped behaviors throughout the educational sessions. The benefits, risks, and implications of the use of SARs for children with ASD are discussed.
... Costa et al. [22] have examined the use of QTrobot in long emotional-ability training for ASD, providing restricted evidence of the positive effects of the robot-mediated intervention. In another study, Costa et al. [23] have evaluated the usefulness of QTrobot by assessing children's attention, imitation, and presence of repetitive and stereotyped behaviors. They obtained significant positive results in all considered parameters. ...
... Another pitfall is the lack of applications in clinical trials. Nowadays, only two studies evaluated the effectiveness of QTrobot in reducing repetitive and stereotyped behaviors and in increasing joint attention and emotional skills in children with ASD [22,23]. ...
Robot-assisted therapy (RAT) is a promising area of translational neuroscience for children
with autism spectrum disorders (ASDs). It has been widely demonstrated that this kind of advanced technological tool provides a reliable and efficient intervention for promoting social skills and communication in children with ASD. This type of treatment consists of a human-assisted social robot acting as an intervention mediator to increase competence and skills in children with ASD. Several social robots have been validated in the literature; however, an explicit technical comparison among devices has never been performed. For this reason, in this article, we provide an overview of the main commercial humanoid robots employed for ASD children with an emphasis on indications for use, pitfalls to be avoided, and recent advances. We conclude that, in the near future, a new generation of devices with high levels of mobility, availability, safety, and acceptability should be designed for improving the complex triadic interaction among teachers, children, and robots.
... Verbal imitation and emotional expression imitation were categorized as studies under social/communication. EC1 were used to filter articles that focuses more on the robot's hardware and technology itself. These two criteria were defined as we believe that evidence collected from the past decade [22,[95][96][97] has proven on ASDC's fascination with robot and technology. ...
Increasing interest on autism brings about prospect of use of Human-Robot Interaction (HRI) method as an assistive tool for therapy. This article presents a review of contemporary topic related to HRI studies to facilitate the improvement of joint attention and imitation skill for ASD children. This review highlights the relevance of past research. Discussion includes experimental design of HRI platforms, methodological steps, test subjects selection, study measures, and the outcomes. We limit studies from the past 10 years to give a clear insight on current state of art technologies. The results are presented such that new or experienced researchers may gain insight on state-of-the-art HRI development for ASD children and help HRI-based interventions meet clinical standards. As results, studies suggest that the use of HRI contributes to positive implications, especially in gaining attention from ASD subjects during therapy sessions. That is, ASD children initiated more social interactions with a robotic partner than a human partner. Thus, it can be concluded that robots have a huge potential to be used as a tool for a therapist to connect with ASD children easily. Future studies might focus on developing a more autonomous HRI so that the robots are capable to operate independently with minor intervention by humans.
... Qualitative measures of attention have been extensively used in research and clinical practice in the ASD field. However, most of these measures are based on manual video processing [14], [15], which is prohibitively time-consuming, operatordependent, and poorly reliable/accurate. Recent studies have focused on obtaining reliable, objective, and quantitative measures of attention based on the head orientation [6], [8], the detection of facial landmarks [16] and/or the eye gaze direction [9], [10]. ...
Children with Autism Spectrum Disorder (ASD) show severe attention deficits, hindering their capacity to acquire new skills. The automatic assessment of their attention response would provide the therapists with an important biomarker to better quantify their behaviour and monitor their progress during therapy. This work aims to develop a quantitativemodel, to evaluate the attention response of children with ASD, during robotic-assistive therapeutic sessions. Previous attempts to quantify the attention response of autistic subjects during human-robot interaction tasks were limited to restrained child movements. Instead, we developed an accurate quantitative system to assess the attention of ASD children in unconstrained scenarios. Our approach combines gaze extraction (Gaze360 model) with the definition of angular Areas-of-Interest, to characterise periods of attention towards elements of interest in the therapy environment during the session. The methodology was tested with 12 ASD children, achieving a mean test accuracy of 79.5 %. Finally, the proposed attention index was consistent with the therapists’ evaluation of patients, allowing a meaningful interpretation of the automatic evaluation. This encourages the future clinical use of the proposed system.
... Other evidence evaluated behavioural differences of participants with ASD between the two types of agents. One study indicated that, during an imitation task, participants with ASD directed more attention to the robot and exhibited fewer stereotyped behaviours (Costa et al., 2018). Furthermore, three studies indicated that individuals with ASD tend to focus more on the robot than a human, showing a particular preference for the robot's eye area (Bekele et al., 2013(Bekele et al., , 2014Yoshikawa et al., 2019). ...
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.
... This is especially beneficial for children with special needs. For instance, socially assistive robots proved more effective in reducing repetitive and stereotyped behaviours in autistic children compared to interactions with people (Costa et al., 2018). In the case of autism spectrum disorder, educational games are being used to enhance children's ability to distinguish emotions in a simulated learning environment, aiming to facilitate their transition between the virtual and realworld contexts (Epp & Makos, 2013). ...
In the last decade, research on the use of artificial intelligence technologies in education has steadily grown. Many studies have demonstrated the potential of these technologies to improve school administration processes, enhance students' learning experiences, simplify teachers' daily tasks, and broaden opportunities for lifelong learning. However, the enthusiasm surrounding these possibilities may overshadow the ethical challenges posed by these systems. This systematic literature review is designed to explore the ethical dimensions surrounding the utilisation of these technologies within the defined timeframe (2011–022) in the field of education. It undertakes a thorough analysis of various applications and objectives, with a particular focus on pinpointing any inherent shortcomings within the existing body of literature. The paper discusses how cultural differences, inclusion, and emotions have been addressed in this context. Finally, it explores the capacity building efforts that have been put in place, their main targets, as well as guidelines and frameworks available for the ethical use of these systems. This review sheds light on the research's blind spots and provides insights to help rethink education ethics in the age of AI. Additionally, the paper explores implications for teacher training, as educators play a critical role in ensuring the ethical use of AI in education. This review aims to stimulate ethical debates around artificial intelligence that recognise it as a non-neutral tool, and to view it as an opportunity to strengthen the debates on the ethics of education itself.
... A first step toward this aim is to automatize therapy, as in modern versions of ELiZA. initiatives with complex graphical user interfaces emulating therapists have shown promising results in cognitive treatments (Stratou et al. 2015). in some cases, paradoxically, empathic virtual agents and empathetic robots may be even more effective compared with human therapies as, for many reasons (including privacy, stress, and distraction), people may feel more comfortable with them in talking about private and sensitive issues (Costa et al. 2018). Digital therapy has also proven to be an effective procedure for treatment of substance abuse (Waltz 2018). ...
While technology has dramatically changed medical practice, various aspects of mental health practice and diagnosis remain almost unchanged across decades. Here we argue that artificial intelligence — with its capacity to learn and infer from data the workings of the human mind — may rapidly change this scenario. However, this process will not happen without friction and will promote an explicit reflection of the overarching goals and foundational aspects of mental health. We suggest that the converse relation is also very likely to happen. The application of artificial intelligence to a field that relates to the foundations of what makes us human — our volition, our thoughts, our pains and pleasures — may shift artificial intelligence back to its earliest days, when it was mostly conceived of as a laboratory to explore the limits and possibilities of human intelligence.
... Also, the robot can be used to monitor a child's progress by providing a means to store data and analytics regarding their behavior. (22,23). Floreo's VR is an example of the use of AI in the treatment of ASD, it provides a platform via which the user learns to engage in specific, realistic settings and situations thus developing their behavioral and social skills which are applicable in day-to-day activities. ...
Autism Spectrum Disorder (ASD) is normally detected and diagnosed by 18 months of age, the process is lengthy and often delayed as it is not considered to be urgent. Artificial Intelligence (AI) can facilitate early diagnosis of autism which would then vastly increase the chances of reducing social impairment in patients by enabling timely intervention. AI can also play a pivotal role in intervention via robots and virtual reality (VR), which can provide a safe means of practicing their social skills before applying them to humans. Additionally, AI provides the hope of making revelations at a genomic level that could aid in the prediction of the development of autism in the antepartum period, or maybe even as a potential pre-conception test.
... Several robots have been proposed exclusively for children with ASD, such as KASPAR [31], Leka [32], QTrobot [11], Milo [33], Buddy [34], Castor [35], and Moxie [10]. Most of them are humanoid in appearance, while Leka is a multisensory spherical robot that emits subtle vibrations, lights up with colorful LEDs, plays music, and chirps in an anthropomorphic fashion. ...
Children with autism spectrum disorder (ASD) have deficits in social interaction and expressing and understanding emotions. Based on this, robots for children with ASD have been proposed. However, few studies have been conducted about how to design a social robot for children with ASD. Non-experimental studies have been carried out to evaluate social robots; however, the general methodology that should be used to design a social robot is not clear. This study proposes a design path for a social robot for emotional communication for children with ASD following a user-centered design approach. This design path was applied to a case study and evaluated by a group of experts in psychology, human–robot interaction, and human–computer interaction from Chile and Colombia, as well as parents of children with ASD. Our results show that following the proposed design path for a social robot to communicate emotions for children with ASD is favorable.
... Costa et al. [161] introduced QTrobot, a social robot developed to assist children with ASD to focus their attention, imitate positive behavior, and reduce repetitive and stereotyped behaviors. QTrobot converses with the child and plays imitation games with the child. ...
In recent years, conversational agents (CAs) have become ubiquitous and are a presence in our daily routines. It seems that the technology has finally ripened to advance the use of CAs in various domains, including commercial, healthcare, educational, political, industrial, and personal domains. In this study, the main areas in which CAs are successful are described along with the main technologies that enable the creation of CAs. Capable of conducting ongoing communication with humans, CAs are encountered in natural-language processing, deep learning, and technologies that integrate emotional aspects. The technologies used for the evaluation of CAs and publicly available datasets are outlined. In addition, several areas for future research are identified to address moral and security issues, given the current state of CA-related technological developments. The uniqueness of our review is that an overview of the concepts and building blocks of CAs is provided, and CAs are categorized according to their abilities and main application domains. In addition, the primary tools and datasets that may be useful for the development and evaluation of CAs of different categories are described. Finally, some thoughts and directions for future research are provided, and domains that may benefit from conversational agents are introduced.
... Initially, the robot tells a story, which is related to the four basic emotions (anger, happiness, sadness, fear), to the child and then invites them to play an imitation game with it (Costa et al., 2018). The robot takes various expressions and asks the child to do the same (saying: Now it's your turn). ...
This is an observational study using descriptive methods and following the guidelines of cross-sectional studies. Taking into account that the children’s needs and abilities are continuously changing, the authors proposed robot-based interventions to enhance independent living skills. Social robots as intervention and therapy agents for children with Autism Spectrum Disorders have been around for quite some time and recent technological advances have brought many changes in their potential and therefore, their popularity. In this article the authors present a panda-robot designed for children with ASD describing its physical appearance, giving information about its features and the ways it can be implemented in an intervention program that is structured in four axes. These four axes include activities that aim towards the development of social, communication, and motor skills and also focus on the implementation of relief and relaxation techniques for children with ASD. Essential guidelines and instructions, as well as certain points of attention, are also discussed.
... Keepon has four degrees of freedom, and it expresses its state of mind through gestures. QTrobot is a robot designed by artificial intelligence with a liquid crystal display face and a robot arm made by LuxAI [29]. It enhances the emotion recognition abilities of autistic children by imitating the emotions of children with expressive faces and moving arms. ...
The use of non-industrial robots, called service robots, is increasing in the welfare fields to meet the demand for robot therapy among individuals with autism. The more simple communication structures and repetitive behaviors of robots, compared to humans, make it easier for children with autism to interpret communication and respond appropriately. Interacting with a robot allows for social distance to be designed and maintained depending on a person’s social interaction needs. To simulate natural social interactions, robots need to perform social distance in some way. In the context of interacting with autistic children, understanding their social response levels is crucial for the robot to implement decisions regarding the distance kept during the interaction. In this study, an experiment was conducted to examine the accuracy of a detection program and explore the correlations between the social responsiveness of children and social distance, wherein 15 autistic children interacted with a robot on a one-to-one basis for about 20 min. The results revealed that both programs implemented in the robot-assisted autism therapy were effective in detecting social distance in a natural HRI situation.
... The 63 cm tall robot, created by LuxAI [13], is a social robot with 12 degrees of freedom. The QTrobot robot consists of a screen with which it expresses its emotions. ...
... The QTrobot was used in [86] that included children with ASD. This robot is a childsized humanoid robot, with an expressive social appearance and a screen that allows the presentation of animated faces. ...
In recent years, social robots have become part of a variety of human activities, especially in applications involving children, e.g., entertainment, education, companionship. The interest of this work lies in the interaction of social robots with children in the field of special education. This paper seeks to present a systematic review of the use of robots in special education, with the ultimate goal of highlighting the degree of integration of robots in this field worldwide. This work aims to explore the technologies of robots that are applied according to the impairment type of children. The study showed a large number of attempts to apply social robots to the special education of children with various impairments, especially in recent years, as well as a wide variety of social robots from the market involved in such activities. The main conclusion of this work is the finding that the specific field of application of social robots is at the first development step; however, it is expected to be of great concern to the research community in the coming years.
... In particular, they have been used to teach social skills [8,13,16]. Studies of robot-assisted interventions with children with ASD report that the robot has a positive effect on the child's engagement, joint attention, imitation and communication [11,30]. In return the use of robots can enhance the learning outcome, as engagement considered to be an important prerequisite for learning, where higher engagement results in more opportunities for social skill learning [16,30]. ...
People with dementia (PwD) often exhibit behavioral, physiological and social symptoms that affect their relationships and reduce their quality of life. Socially assistive robots (SARs) have proven effective in reducing some of these symptoms. However, the design of SARs for dementia care remains a challenging task. In this paper, we present a human-centered design framework to assist researchers, designers, and roboticist from the conceptualization of engaging prototypes of SARs until the assessment of their efficacy at producing dementia-relevant health outcomes. The framework incorporates several key principles of a Human-Centered Artificial Intelligence (HCAI) approach. It incorporates the needs and perspectives of the different stakeholders into the design and evaluation of the interactions. It fosters accessibility and inclusion thru personalization and encourages human-robot collaboration by facilitating natural and engaging interactions that build trust and rapport. We illustrate the use of the framework with the design of a SAR to support a Cognitive Stimulation Therapy. From this case study we derive a set of design insights for the development of SARs behaviors and interactions for dementia care.
Robots are thought to be able to address some of society’s challenges in autism care and education. Robots may extand services and provide them in personalized, repeated, and playful ways. However, it is still largely unknown to what extent professionals intend to use robots and what determines their intentions. Using the Theory of Planned Behaviour framework, we aimed to better understand the determinants behind professionals’ intentions to use robots with their clients with autism. We conducted an online survey, to which 447 professionals (e.g., psychologists) working with people with autism answered. Our results indicate moderate and well-predicted intentions for the enquired professionals to use a robot with their clients with autism. We found that attitude and perceived social norms are the main predictors of their intentions. Our results also point to the significant and positive influence of moral norms on the attitudes of professionals. Additionally, our preliminary analysis of underlying beliefs to the assessed predictors of intention enables a better understanding on how professionals perceive the place of robots in their work. These results can inspire roboticists who want to build assistive robots for the real world and guide stakeholders when implementing such robots in the health and education sectors.
Leveraging advancements in information technology and the inherent interest of children with autism in robots and technology, this study explores the crucial role of analyzing application logs in enhancing therapy experiences for children with autism. By examining these logs, valuable insights can be obtained, enabling performance tracking, evidence-based evaluation, personalization of interventions, and continuous improvement. This will allow us to get more information about children’s preferences and behavior even when we are not in direct contact with them, by extending onsite robot therapies to the home environment. This research contributes to the understanding of the transformative power of log analysis and its implications for optimizing therapy experiences and advancing treatment for children with autism.
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.
هدفت الدراسة إلى بيان أثر برنامج تدريبي قائم على برامج التأهيل المهني والدعم العاطفي في خفض السلوكيات النمطية لدى طلاب اضطراب طيف التوحد المدمجين بمراكز الدمج الحكومية بدولة قطر، طبقت الدراسة على عينة من طلاب اضطراب طيف التوحد بنين وبنات قدرها (35 طالب وطالبة) مدمجين بمراكز الدمج الحكومية بالمرحلة الثانوية بدولة قطر، استخدمت الدراسة مقياس السلوكيات النمطية كأداة لتقدير شدة السلوكيات النمطية، وبرنامج تدريسي للتأهيل المهني لطلاب اضطراب طيف التوحد المدمجين بالمدارس الحكومية، حيث تم تطبيق القياس القبلي للسلوكيات النمطية قبل تطبيق البرنامج، وتم تنفيذ برنامج التأهيل المهني مع الدعم العاطفي من قبل المعلمين وأولياء الأمور، أثبتت نتائج القياس البعدي للسلوكيات النمطية انخفاض السلوكيات النمطية لدى عينة الدراسة بصورة دالة إحصائية. وقد أوصت الدراسة بتفعيل البرامج التي تشغل طلاب التوحد عن السلوكيات النمطية بما يساهم في خفضها وعلاجها.
The study aimed to demonstrate the effect of a training program based on vocational rehabilitation and emotional support programs in reducing stereotypical behaviors among autism spectrum disorder students integrated into government integration centers in the State of Qatar. The study was applied to a sample of autism spectrum disorder students, boys, and girls, amounting to (35 male and female students) integrated into integration centers. At the government secondary level in the State of Qatar, the study used the Stereotypic Behavior Scale as a tool to estimate the severity of stereotypic behaviors, and a teaching program for vocational rehabilitation for students with autism spectrum disorder integrated into government schools, where a pre-measurement of stereotypic behaviors was applied before implementing the program, and a vocational rehabilitation program with emotional support was implemented by Teachers and parents, the results of the post-measurement of stereotypical behaviors demonstrated a statistically significant decrease in stereotypical behaviors among the study sample. The study recommended activating programs that distract students with autism from stereotypical behaviors, thus contributing to their reduction and treatment.
We designed a coordination–cooperation game dedicated to teaching the theory of mind (ToM) to children with autism spectrum disorder. Children interacted with either a robot or a human. They had to coordinate their gestures with the beats of a ditty sung by their partner (coordination), who then implicitly asked them for help (cooperation). Before and after this cooperation–coordination task, the children performed a helping task that assessed their ToM skills: the ability to infer social partners’ intentions. Despite the regularity and predictability of the robot, children made the most progress in the helping task after interacting with a human. Motor coupling was more stable in child–human than in child–robot dyads. The ability of the social partner to actively maintain a stable social coupling seems to be a primary factor inciting the child to learn and transfer the just-practiced social skills.
In this chapter, the author introduces and expands upon the use of robots for social assistance with children who have autism spectrum disorders and other similar conditions. The social skills these robots can assist autistic children with are identified, and five specific robots (NAO, Milo, Kaspar, QTrobot, and Moxie) developed for use with autistic children are reviewed. Each robot is described in terms of specifications functionality and price, and a practical example of its use is also included. Additionally, advantages, disadvantages, and research-based outcomes are discussed.
Children with Autism Spectrum Disorder have deficits in social interaction and expressing and understanding emotions. Many robots for children with ASD have been proposed. However, few studies were found about how to design a social robot for children with ASD. Studies reviewed employed non-experimental studies to evaluate a social robot, but the methodology to design a social robot is rare. This study proposes a design path for a social robot for emotional communi-cation for children with ASD, following User-Centered Design approach. This design path is ap-plied with a study case, evaluated with an expert group on psychologist, human-robot interaction, human-computer interaction, and parents of children with ASD. Results show than following the design path proposed to design a social robot to communication emotions for children ASD is favorable.
Research in the area of Human-robot Interaction (HRI) has gained momentum in recent years. The robot-based intervention system has spread to help the less fortunate specifically children who suffer from Autism Spectrum Disorder (ASD). These robot-based intervention studies utilized HRI platform in improving the impaired skills, such as, social skills, motor skills, and behavior. Recently, robot-based therapies have shown encouraging outcomes in improving the social skills of Autism Spectrum Disorder Children (ASDC). Herein, this paper elaborates a pilot study on initial responses of ASDC when being introduced to a humanoid QTrobot. QTrobot is chosen because of its ability to show facial expression. The ability to subtly show emotion is very important as it is going to be used for our differential reinforcement technique. The pilot experiment consists of 5 simple modules to prompt the responses of the participants. From the results, it clearly can be seen that humanoid QTrobot has a potential to be an HRI platform to initiate interaction among ASDC.
Humanoid robots have shown to provide interesting perspectives for autistic children. Yet, few studies have looked at educators' point of view on the use of such robots in educational settings. This paper presents a case study of the use of a humanoid robot, NAO, in a French preschool class dedicated to autistic children. Our work focuses on the perspectives of the adults working with these children. We interviewed the professional staff about changes in their teaching due to the presence of the robot, about the effects on the pupils' behaviour, and about the collaboration between the special needs teacher, the special needs support worker and the operational specialist from the digital education department of the district academic head office. Four themes were identified: joint reflection and collaboration when working with NAO, working with NAO, impact of NAO on pupils, impact of NAO on adults. The professionals underscored the necessity of adopting certain attitudes, in particular, the most neutral facial expression possible, so as not to disturb the children's learning process. They were under the impression that the robot had a beneficial effect on the pupils in terms of learning and social skills, and that it facilitated collaboration among them.
Joint attention is the capacity of sharing attention between two agents and an aspect of the environment, through the use of different cues, namely gaze. This capacity is of paramount importance for social skills. People with Autism Spectrum Disorder (ASD) present certain deficits in joint attention. Therefore, there is an increasing interest in finding therapies to improve this skill. Some of these therapies include robots since they are known to be attractive to people with autism due to their motivation ability and predictability when compared with humans. In this line, we have designed a real-time attention classifier for a triadic robotic therapy, using Gaze360 and geometrical considerations of the scene. We were able to classify the gaze of the therapist and the one of the child during the whole session, even in a highly unconstrained scenario with a single camera, achieving a mean accuracy of 59%. This classifier can be used for the measurement of joint attention, an important metric for the development of adaptive robotic therapies, where increasing levels of difficulty and engagement are provided dependent on the ASD children, who are characterised by high heterogeneity. Future work will pass by the calculation of this metric and integration on a robotic platform for ASD therapy to understand the impact of these robotic therapies in improving ASD symptoms, specifically on how ASD children share their attention with other people present in the rehabilitation scenarios.
Autism Spectrum Disorder (ASD) is characterized by deficits in social and communication skills as well as restrictive and repetitive behavioral patterns. A variety of challenging behaviors in children with ASD and persistent non-compliance with daily requirements may be associated with delay in the development of social skills and impairing social relations, with an adverse effect on the educational process and on the self-esteem of individuals. To this aim, there is a need for appropriate interventions, targeted at reducing these behaviors. Robot-mediated interventions (ROMI) can be advantageous for children with ASD, who often show an increased interest in technology enhanced interventions. Research focusing on the effect of ROMI on challenging behaviors in children with ASD has been limited. For this purpose, it was conducted a review of studies that empirically tested the usefulness of ROMI in managing challenging behaviors in children with ASD. A literature search was made in five databases using keywords pertaining to robots, ASD, challenging behaviors, and interventions. Nine studies were reviewed which met the inclusion criteria. The findings of these studies indicate that ROMI show promise in reducing challenging behaviors such as tantrums, repetitive and stereotyped behaviors, inappropriate behaviors in transitions. In terms of noncompliance, mixed results were presented. Further research is needed to explore the usefulness of robots both in reducing challenging behaviors of children with ASD and in preventive exercises in early intervention programs for this population.
Educational robotics plays a significant role in modern society. Teachers increasingly use technological tools to study Science, Technology, Engineering, Arts, Mathematics (STEAM) and other fields, such as problem-solving, environment, teamwork, and language learning. The design of an educational robot is the key to make this tool more interesting for students and more efficient for teachers. Dimensions, stability, sensors, and generally, the philosophy of the design process is the base of the robot’s success. This paper presents an innovative educational robot that is designed for utilizing empathy.
In this work, a bionic memristive circuit with functions of emotional evolution is proposed by mimicking the emotional circuit in limbic system, which can perform unconscious and conscious emotional evolutions by using theories of internal regulation and external stimulation respectively. Two kinds of memristive models, volatile and non-volatile, play key roles in the process of emotional evolution. That is, the internal regulation is mainly responsible for simulating the unconscious evolution process over time by using the forgetting effect of the volatile memristor. The external stimulation is mainly responsible for using the memristance plasticity of the non-volatile memristor to simulate the evolutionary learning behavior under the action of multi-modal inputs (such as visual, speech and text signals), so as to realize the conscious emotional evolution. A two-dimensional (2D) emotional state space consisted of valence and arousal signals is adopted, the evolution behaviors are performed on the basis of valence and arousal signals in the space, in order to achieve continuous emotional evolution and express the evolved emotions intuitively. Due to the uses of memristors, the proposed circuit can realize in-memory computing, which fundamentally avoids the problem of storage wall and constructs a brain-inspired information processing architecture. The simulation results in PSPICE show that a nonlinear mapping relationship between inputs and outputs is constructed through the proposed circuit, which can carry out diversified emotional evolution based on the designed internal regulation and external stimulation evolution circuits.
Autism spectrum disorder (ASD) is a life-long neurological disability, and a cure has not yet been found. ASD begins early in childhood and lasts throughout a person’s life. Through early intervention, many actions can be taken to improve the quality of life of children. Robots are one of the best choices for accompanying children with autism. However, for most robots, the dialogue system uses traditional techniques to produce responses. Robots cannot produce meaningful answers when the conversations have not been recorded in a database. The main contribution of our work is the incorporation of a conversation model into an actual robot system for supporting children with autism. We present the use a neural network model as the generative conversational agent, which aimed at generating meaningful and coherent dialogue responses given the dialogue history. The proposed model shares an embedding layer between the encoding and decoding processes through adoption. The model is different from the canonical Seq2Seq model in which the encoder output is used only to set-up the initial state of the decoder to avoid favoring short and unconditional responses with high prior probability. In order to improve the sensitivity to context, we changed the input method of the model to better adapt to the utterances of children with autism. We adopted transfer learning to make the proposed model learn the characteristics of dialogue with autistic children and to solve the problem of the insufficient corpus of dialogue. Experiments showed that the proposed method was superior to the canonical Seq2sSeq model and the GAN-based dialogue model in both automatic evaluation indicators and human evaluation, including pushing the BLEU precision to 0.23, the greedy matching score to 0.69, the embedding average score to 0.82, the vector extrema score to 0.55, the skip-thought score to 0.65, the KL divergence score to 5.73, and the EMD score to 12.21.
Pavlov conditioning is a typical associative memory, which involves associative learning between the gustatory and auditory cortex, known as Pavlov associative memory. Inspired by neural mechanisms and biological phenomena of Pavlov associative memory, this paper proposes a multi-functional memristive Pavlov associative memory circuit. In addition to learning and forgetting, whose rates change with the number of associative learning times, the circuit also achieves other innovative functions. First, consolidation learning, which refers to the continued learning process after acquiring associative memory, changes the rates of learning and forgetting. Secondly, the natural forgetting rate tends to zero when the associative memory has been acquired several times, which means the formation of longterm memory. Thirdly, the generalization and differentiation of associative memory caused by similar stimuli are realized through a simplified memristive feedforward neural network. Besides, this circuit implements the associative learning function of interval stimuli through a simpler structure. The above functions are realized by time interval module, variable rates module, and generalization & differentiation module. It has been shown that the proposed circuit has good robustness, and can reduce the influence of parasitic capacitance, memristive conductance drift, and input noise on circuit functions. Through further research, this circuit is expected to be used in robot platforms to realize human-like perception and associative cognitive functions.
During the last two decades, the use of Information and Communication Technologies (ICT) has opened new paths in the intervention of people with Autism Spectrum Disorder (ASD). These may include intervention based on "social robots". This research aims to review the state of scientific production on social robotics in the intervention of students with ASD during 2000–2019 to establish an action protocol in the use of this tool through a list of bibliometric indicators. To achieve this objective, we worked through the main collection of the Web of Science (WoS), obtaining a sample of 69 articles.The results indicate that the authors with the highest scientific production are American, even though they do not own the most cited articles in the field. In this sense, the great number of publications are indexed in the JCR Q1. Likewise, two journals are the work core of the field of study. Moreover, the vast majority of the studies are focused in different areas such as: communication and social interaction, repeated and stereotyped patterns of behaviour, interest, or activity. As a conclusion, robotics is a tool increasingly used by students with ASD. Moreover, robotics can be applied through a protocol based on the indicators analyzed. Therefore, future researchers in the field would use the indicators to determine, for example, which area to work in, which year they could obtain information or which journals publish the highest quality research. With the information provided by these indicators, a robotic intervention could be implemented.
The present work is a collaborative research aimed at testing the effectiveness of the robot-assisted intervention administered in real clinical settings by real educators. Social robots dedicated to assisting persons with autism spectrum disorder (ASD) are rarely used in clinics. In a collaborative effort to bridge the gap between innovation in research and clinical practice, a team of engineers, clinicians and researchers working in the field of psychology developed and tested a robot-assisted educational intervention for children with low-functioning ASD (N = 20) A total of 14 lessons targeting requesting and turn-taking were elaborated, based on the Pivotal Training Method and principles of Applied Analysis of Behavior. Results showed that sensory rewards provided by the robot elicited more positive reactions than verbal praises from humans. The robot was of greatest benefit to children with a low level of disability. The educators were quite enthusiastic about children's progress in learning basic psychosocial skills from interactions with the robot. The robot nonetheless failed to act as a social mediator, as more prosocial behaviors were observed in the control condition, where instead of interacting with the robot children played with a ball. We discuss how to program robots to the distinct needs of individuals with ASD, how to harness robots' likability in order to enhance social skill learning, and how to arrive at a consensus about the standards of excellence that need to be met in interdisciplinary co-creation research. Our intuition is that robotic assistance, obviously judged as to be positive by educators, may contribute to the dissemination of innovative evidence-based practice for individuals with ASD.
In this work, a memristive circuit with affective multi-associative learning function is proposed, which mimics the process of human affective formation. It mainly contains three modules: affective associative learning, affective formation, affective expression. The first module is composed of several affective single-associative learning circuits consisting of memristive neurons and synapses. Memristive neuron will be activated and output pulses if its input exceeds the threshold. After it is activated, memristive neuron can automatically return to the inactive state. Memristive synapse can realize learning and forgetting functions based on the signals from pre- and post-neurons. The learning rule is pre-neuron activated lags behind post-neuron for a short time; the forgetting rule is to repeatedly activate pre-neuron after the emotion is learned. The process of learning or forgetting corresponds to facilitating or inhibiting synaptic weight, that is, decreasing or increasing memristance continuously. Different voltage signals applied to memristors and different parameters of memristors would lead to different synaptic weights which indicate different affective association. The second module can convert affective signals to corresponding emotions. The formed emotions can be shown in a face by the third module. The simulation results in PSPICE show that the proposed circuit system can learn, forget and form emotions like human. If the proposed circuit is further used on a humanoid robot platform through further research, the robot will have the ability of affective interaction with human so that it can be effectively used in affective company and other aspects.
Socially assistive robots, when used in a way that takes into consideration children's needs and developmental characteristics, can be useful tools to enable children's development. More specifically, due to their characteristics (predictability, simplicity, and repetition) robots can be especially helpful to teach emotional abilities to children with autism spectrum disorder (ASD). Previous research has provided preliminary evidence that robots can help children improve in some domains such as joint attention and imitation. However, no studies have examined how robots can be integrated in intervention protocols targeting the acquisition of emotional abilities in children with ASD. This paper presents a work in progress on an emotional ability training developed for children with ASD using the QT socially assistive robot. This training aims to test whether children with ASD can benefit from a robot-mediated training to improve emotional ability.
The aim of the study was to investigate the effectiveness of a brief robot-mediated intervention based on Lego(®) therapy on improving collaborative behaviors (i.e., interaction initiations, responses, and play together) between children with ASD and their siblings during play sessions, in a therapeutic setting. A concurrent multiple baseline design across three child-sibling pairs was in effect. The robot-intervention resulted in no statistically significant changes in collaborative behaviors of the children with ASD. Despite limited effectiveness of the intervention, this study provides several practical implications and directions for future research.
Autistic children are often impaired in initiating and responding to Joint Attention. In recent years, there has been an increase in the application of robots in diagnosis and treatment of autism. The purpose of the current research has been primarily to originate the proper therapeutic scenarios and to implement two interactive humanoid robots as therapy assistants in autism treatment in Iran. To this end, the humanoid robots were programmed and teleoperated via Microsoft Kinect Sensor and PhantomOmni Haptic Robot to elicit reactions consisting of imitation of humans by the humanoid robots and vice versa. In this paper, we elaborate on the therapeutic items that we have designed to improve joint attention and imitation in autistic children through using humanoid robots. Moreover, the fairly promising results of some interventions conducted in a pilot study on four autistic cases will be addressed and discussed. Our research target is to increase social interaction and involve autistic children in dyadic/triadic interactions which seems quite possible due to the findings of the pilot study conducted.
This paper aims to study the role of the social robot Probo in providing assistance to a therapist for robot assisted therapy (RAT) with autistic children. Children with autism have difficulties with social interaction and several studies indicate that they show preference toward interaction with objects, such as computers and robots, rather than with humans. In 1991, Carol Gray developed Social Stories, an intervention tool aimed to increase children’s social skills. Social stories are short scenarios written or tailored for autistic individuals to help them understand and behave appropriately in social situations. This study shows that, in specific situations, the social performance of autistic children improves when using the robot Probo, as a medium for social story telling, than when a human reader tells the stories. The robot tells Social Stories to teach ASD children how to react in situations like saying “hello”, saying “thank you” and “sharing toys”. The robot has the capability of expressing emotions and attention via its facial expressions and its gaze. The paper discusses the use of Probo as an added-value therapeutic tool for social story telling and presents the first experimental results. Keywords: social robot; ASD children; social story; robot assisted therapy
This paper presents a series of 4 single subject experiments aimed to investigate whether children with autism show more social engagement when interacting with the Nao robot, compared to a human partner in a motor imitation task. The Nao robot imitates gross arm movements of the child in real-time. Different behavioral criteria (i.e. eye gaze, gaze shifting, free initiations and prompted initiations of arm movements, and smile/laughter) were analyzed based on the video data of the interaction. The results are mixed and suggest a high variability in reactions to the Nao robot. The results are as follows: For Child2 and Child3, the results indicate no effect of the Nao robot in any of the target variables. Child1 and Child4 showed more eye gaze and smile/laughter in the interaction with the Nao robot compared to the human partner and Child1 showed a higher frequency of motor initiations in the interaction with the Nao robot compared to the baselines, but not with respect to the human-interaction. The robot proved to be a better facilitator of shared attention only for Child1. Keywords: human-robot interaction; assistive robotics; autism
We aimed to compare, during a joint attention (JA) elicitation task, how children with autism spectrum disorder (ASD) and children with typical development (TD) behave and explore their 4 dimensional (meaning spatial 3D + time) when interacting with a human or with a robotic agent.
We built a system that employed a Nao robot and a perception system based on a RGB-D sensor (Kinect) to capture social engagement cues. A JA induction experiment was performed in which children with ASD (N = 16) and matched TD children (N = 16) had a 3-min interaction with the robot or with a therapist. Nao induced JA by gazing; by gazing and pointing; and by gazing, pointing and vocalizing at pictures. Both groups of children performed well with the therapist. However, with Nao, both groups had lower JA scores, and the children with ASD had a significantly lower score than the TD children. We found that (i) multimodal JA induction was more efficient in both groups; (ii) the 3D spatial world gaze exploration showed less accuracy; and (iii) the trunk position in ASD showed less stability in the 4 dimensions compared to TD controls.
We conclude that, in ASD, JA skill depends on the interaction partner, and implies a higher motor and cognitive cost.
Robot-assisted therapy (RAT) is an emerging field that has already seen some success and is likely to develop in the future. One particular application area is within therapies for autism spectrum disorders, in which the viability of the approach has been demonstrated.
The present paper is a vision paper with the aim of identifying research directions in the near future of RAT. Specifically, we argue that the next step in such therapeutic scenarios is the development of more substantial levels of autonomy which would allow the robot to adapt to the individual needs of children over longer periods of time (while remaining under the ultimate supervision of a therapist). We argue that this requires new advances on the level of robot controllers as well as the ability to infer and classify intentions, goals and emotional states of the robot’s interactants. We show that the state of the art in a number of relevant disciplines is now at the point at which such an endeavour can be approached in earnest.
Interactive robots are used increasingly not only in entertainment and service robotics, but also in rehabilitation, therapy and education. The work presented in this paper is part of the Aurora project, rooted in assistive technology and robot-human interaction research. Our primary aim is to study if robots can potentially be used as therapeutically or educationally useful `toys'. In this paper we outline the aims of the project that this study belongs to, as well as the specific qualitative contextual perspective that is being used. We then provide an in-depth evaluation, in part using Conversation Analysis (CA), of segments of trials where three children with autism interacted with a robot as well as an adult. We focus our analysis primarily on joint attention which plays a fundamental role in human development and social understanding. Joint attention skills of children with autism have been studied extensively in autism research and therefore this behaviour provides a relevant focus for our study. In the setting used, joint attention emerges from natural and spontaneous interactions between a child and an adult. We present the data in the form of transcripts and photo stills. The examples were selected from extensive video footage for illustrative purposes, i.e. demonstrating how children with autism can respond to the changing behaviour of their co-participant, i.e. the experimenter. Furthermore, our data shows that the robot provides a salient object, or mediator for joint attention. The paper concludes with a discussion of implications of this work in the context of further studies with robots and children with autism within the Aurora project, as well as the potential contribution of robots to research into the nature of autism.
This article discusses the potential of using interactive environments in autism therapy. We specifically address issues relevant to the Aurora project, which studies the possible role of autonomous, mobile robots as therapeutic tools for children with autism. Theories of mindreading, social cognition and imitation that informed the Aurora project are discussed and their relevance to the project is outlined. Our approach is put in the broader context of socially intelligent agents and interactive environments. We summarise results from trials with a particular mobile robot. Finally, we draw some comparisons to research on interactive virtual environments in the context of autism therapy and education. We conclude by discussing future directions and open issues.
This article studies the impact of a robot's appearance on interactions involv-ing four children with autism. This work is part of the Aurora project with the overall aim to support interaction skills in children with autism, using robots as 'interactive toys' that can encourage and mediate interactions. We follow an approach commonly adopted in assistive robotics and work with a small group of children with autism. This article investigates which robot appearances are suitable to encourage interactions between a robot and children with autism. The children's levels of interaction with and response to different appearances of two types of robots are compared: a small humanoid doll, and a life-sized 'Theatrical Robot' (a mime artist behaving like a robot). The small humanoid robot appeared either as a human-like 'pretty doll' or as a 'robot' with plain features. The Theatrical Robot was presented either as an ordinary human, or with plain clothing and a featureless, masked face. The results of these trials clearly indicate the children's preference in their initial response for interaction with a plain, featureless robot over the interaction with a human-like robot. In the case of the life-size Theatrical Robot, the response of children towards the plain/robotic robot was notably more social and pro-active. Implications of these results for our work on using robots as assistive technology for children with autism and their possible use in autism research are discussed.
We provide a systematic review of epidemiological surveys of autistic disorder and pervasive developmental disorders (PDDs) worldwide. A secondary aim was to consider the possible impact of geographic, cultural/ethnic, and socioeconomic factors on prevalence estimates and on clinical presentation of PDD. Based on the evidence reviewed, the median of prevalence estimates of autism spectrum disorders was 62/10 000. While existing estimates are variable, the evidence reviewed does not support differences in PDD prevalence by geographic region nor of a strong impact of ethnic/cultural or socioeconomic factors. However, power to detect such effects is seriously limited in existing data sets, particularly in low-income countries. While it is clear that prevalence estimates have increased over time and these vary in different neighboring and distant regions, these findings most likely represent broadening of the diagnostic concets, diagnostic switching from other developmental disabilities to PDD, service availability, and awareness of autistic spectrum disorders in both the lay and professional public. The lack of evidence from the majority of the world's population suggests a critical need for further research and capacity building in low- and middle-income countries. Autism Res 2012, ••: ••-••. © 2012 International Society for Autism Research, Wiley Periodicals, Inc.
Autism spectrum disorders are a group of lifelong disabilities that affect people's ability to communicate and to understand social cues. Research into applying robots as therapy tools has shown that robots seem to improve engagement and elicit novel social behaviors from people (particularly children and teenagers) with autism. Robot therapy for autism has been explored as one of the first application domains in the field of socially assistive robotics (SAR), which aims to develop robots that assist people with special needs through social interactions. In this review, we discuss the past decade's work in SAR systems designed for autism therapy by analyzing robot design decisions, human-robot interactions, and system evaluations. We conclude by discussing challenges and future trends for this young but rapidly developing research area.
Unpredictability and complexity of social interactions are important challenges for a low functioning autistic child. The
objective of this research is to study how a mobile robot can, by appearing more predictable, appealing and simple than a
human being, facilitate reciprocal interaction such as imitative play. By conducting an exploratory study involving four children,
we found that forms of shared conventions such as imitation of body movements and of familiar actions are higher with two
children paired with a human mediator, compared to two children paired with a robot mediator. However, the two children paired
with the robot mediator demonstrated increased shared attention (visual contact, physical proximity) and imitate facial expressions
(smile) more than the children paired with the human mediator.
Background:
The spectrum of disorders of the brain is large, covering hundreds of disorders that are listed in either the mental or neurological disorder chapters of the established international diagnostic classification systems. These disorders have a high prevalence as well as short- and long-term impairments and disabilities. Therefore they are an emotional, financial and social burden to the patients, their families and their social network. In a 2005 landmark study, we estimated for the first time the annual cost of 12 major groups of disorders of the brain in Europe and gave a conservative estimate of €386 billion for the year 2004. This estimate was limited in scope and conservative due to the lack of sufficiently comprehensive epidemiological and/or economic data on several important diagnostic groups. We are now in a position to substantially improve and revise the 2004 estimates. In the present report we cover 19 major groups of disorders, 7 more than previously, of an increased range of age groups and more cost items. We therefore present much improved cost estimates. Our revised estimates also now include the new EU member states, and hence a population of 514 million people.
Aims:
To estimate the number of persons with defined disorders of the brain in Europe in 2010, the total cost per person related to each disease in terms of direct and indirect costs, and an estimate of the total cost per disorder and country.
Methods:
The best available estimates of the prevalence and cost per person for 19 groups of disorders of the brain (covering well over 100 specific disorders) were identified via a systematic review of the published literature. Together with the twelve disorders included in 2004, the following range of mental and neurologic groups of disorders is covered: addictive disorders, affective disorders, anxiety disorders, brain tumor, childhood and adolescent disorders (developmental disorders), dementia, eating disorders, epilepsy, mental retardation, migraine, multiple sclerosis, neuromuscular disorders, Parkinson's disease, personality disorders, psychotic disorders, sleep disorders, somatoform disorders, stroke, and traumatic brain injury. Epidemiologic panels were charged to complete the literature review for each disorder in order to estimate the 12-month prevalence, and health economic panels were charged to estimate best cost-estimates. A cost model was developed to combine the epidemiologic and economic data and estimate the total cost of each disorder in each of 30 European countries (EU27+Iceland, Norway and Switzerland). The cost model was populated with national statistics from Eurostat to adjust all costs to 2010 values, converting all local currencies to Euro, imputing costs for countries where no data were available, and aggregating country estimates to purchasing power parity adjusted estimates for the total cost of disorders of the brain in Europe 2010.
Results:
The total cost of disorders of the brain was estimated at €798 billion in 2010. Direct costs constitute the majority of costs (37% direct healthcare costs and 23% direct non-medical costs) whereas the remaining 40% were indirect costs associated with patients' production losses. On average, the estimated cost per person with a disorder of the brain in Europe ranged between €285 for headache and €30,000 for neuromuscular disorders. The European per capita cost of disorders of the brain was €1550 on average but varied by country. The cost (in billion €PPP 2010) of the disorders of the brain included in this study was as follows: addiction: €65.7; anxiety disorders: €74.4; brain tumor: €5.2; child/adolescent disorders: €21.3; dementia: €105.2; eating disorders: €0.8; epilepsy: €13.8; headache: €43.5; mental retardation: €43.3; mood disorders: €113.4; multiple sclerosis: €14.6; neuromuscular disorders: €7.7; Parkinson's disease: €13.9; personality disorders: €27.3; psychotic disorders: €93.9; sleep disorders: €35.4; somatoform disorder: €21.2; stroke: €64.1; traumatic brain injury: €33.0. It should be noted that the revised estimate of those disorders included in the previous 2004 report constituted €477 billion, by and large confirming our previous study results after considering the inflation and population increase since 2004. Further, our results were consistent with administrative data on the health care expenditure in Europe, and comparable to previous studies on the cost of specific disorders in Europe. Our estimates were lower than comparable estimates from the US.
Discussion:
This study was based on the best currently available data in Europe and our model enabled extrapolation to countries where no data could be found. Still, the scarcity of data is an important source of uncertainty in our estimates and may imply over- or underestimations in some disorders and countries. Even though this review included many disorders, diagnoses, age groups and cost items that were omitted in 2004, there are still remaining disorders that could not be included due to limitations in the available data. We therefore consider our estimate of the total cost of the disorders of the brain in Europe to be conservative. In terms of the health economic burden outlined in this report, disorders of the brain likely constitute the number one economic challenge for European health care, now and in the future. Data presented in this report should be considered by all stakeholder groups, including policy makers, industry and patient advocacy groups, to reconsider the current science, research and public health agenda and define a coordinated plan of action of various levels to address the associated challenges.
Recommendations:
Political action is required in light of the present high cost of disorders of the brain. Funding of brain research must be increased; care for patients with brain disorders as well as teaching at medical schools and other health related educations must be quantitatively and qualitatively improved, including psychological treatments. The current move of the pharmaceutical industry away from brain related indications must be halted and reversed. Continued research into the cost of the many disorders not included in the present study is warranted. It is essential that not only the EU but also the national governments forcefully support these initiatives.
Individuals with autistic spectrum disorders (ASDs) often experience, describe and exhibit unusual patterns of sensation and attention. These anomalies have been hypothesized to result from overarousal and consequent overfocused attention. Parents of individuals with ASD rated items in three domains, 'sensory overreactivity', 'sensory underreactivity' and 'sensory seeking behaviors', of an expanded version of the Sensory Profile, a 103-item rating scale developed for the present study. Parents also rated symptom severity, overselective attention and exceptional memory, and completed the Vineland Adaptive Behavior Scales. Of 222 rated subjects, 144 had complete data. Cluster analysis showed the predicted overfocused pattern of sensation and attention, comprising overreactivity, perseverative behavior and interests, overfocused attention and exceptional memory in 43 percent of this sample. This pattern was striking in 10 percent. The neurological basis of overreactivity and overfocusing is discussed in relation to the overarousal hypothesis. Attention is drawn to its considerable prevalence in the ASD population.
The existence of a specialized imitation module in humans is hotly debated. Studies suggesting a specific imitation impairment in individuals with autism spectrum disorders (ASD) support a modular view. However, the voluntary imitation tasks used in these studies (which require socio-cognitive abilities in addition to imitation for successful performance) cannot support claims of a specific impairment. Accordingly, an automatic imitation paradigm (a 'cleaner' measure of imitative ability) was used to assess the imitative ability of 16 adults with ASD and 16 non-autistic matched control participants. Participants performed a prespecified hand action in response to observed hand actions performed either by a human or a robotic hand. On compatible trials the stimulus and response actions matched, while on incompatible trials the two actions did not match. Replicating previous findings, the Control group showed an automatic imitation effect: responses on compatible trials were faster than those on incompatible trials. This effect was greater when responses were made to human than to robotic actions ('animacy bias'). The ASD group also showed an automatic imitation effect and a larger animacy bias than the Control group. We discuss these findings with reference to the literature on imitation in ASD and theories of imitation.
This study examined repetitive and stereotyped behaviors (RSB) in children with autism spectrum disorders (ASD, n = 50), developmental delays without ASD (DD; n = 25) and typical development (TD, n = 50) between 18 and 24 months of age. Children with ASD demonstrated significantly higher frequency and longer duration of RSB with objects, body, and sensory behaviors during a systematic behavior sample than both the DD and TD groups. RSB with objects were related to concurrent measures of symbolic capacity and social competence in the second year and predicted developmental outcomes as well as severity of autism symptoms at 3 years in children with communication delays. RSB in the second year appear to be important for early identification and prediction of developmental outcomes.
Researchers have been placing an increased importance on discovering what variables contribute to better prognosis during behavioral interventions for children with autism. This article preliminarily identifies sleep problems that may exacerbate symptoms of autism; thus, possibly influencing effectiveness of daytime interventions. A data-base of parent report of sleep problems of children with autism ( N =55), ranging from 5 to 12 years of age ( M =8.2 years) was evaluated. Results suggested that fewer hours of sleep per night predicted overall autism scores and social skills deficits. Similarly, stereotypic behavior was predicted by fewer hours of sleep per night and screaming during the night. Increased sensitivity to environmental stimuli in the bedroom and screaming at night predicted communication problems. Finally, sensitivity to environmental stimuli in the bedroom also predicted fewer developmental sequence disturbances. The results indicate that sleep problems and the diagnostic characteristics of autism may be related. However, future research must be completed to determine the specific relationship.
Increasingly researchers are attempting to develop robotic technologies for children with autism spectrum disorder (ASD). This pilot study investigated the development and application of a novel robotic system capable of dynamic, adaptive, and autonomous interaction during imitation tasks with embedded real-time performance evaluation and feedback. The system was designed to incorporate both a humanoid robot and a human examiner. We compared child performance within system across these conditions in a sample of preschool children with ASD (n = 8) and a control sample of typically developing children (n = 8). The system was well-tolerated in the sample, children with ASD exhibited greater attention to the robotic system than the human administrator, and for children with ASD imitation performance appeared superior during the robotic interaction.
Importance
The economic effect of autism spectrum disorders (ASDs) on individuals with the disorder, their families, and society as a whole is poorly understood and has not been updated in light of recent findings.Objective
To update estimates of age-specific, direct, indirect, and lifetime societal economic costs, including new findings on indirect costs, such as individual and parental productivity costs, associated with ASDs.Design, Setting, and Participants
A literature review was conducted of US and UK studies on individuals with ASDs and their families in October 2013 using the following keywords: age, autism spectrum disorder, prevalence, accommodation, special education, productivity loss, employment, costs, and economics. Current data on prevalence, level of functioning, and place of residence were combined with mean annual costs of services and support, opportunity costs, and productivity losses of individuals with ASDs with or without intellectual disability.Exposure
Presence of ASDs.Main Outcomes and Measures
Mean annual medical, nonmedical, and indirect economic costs and lifetime costs were measured for individuals with ASDs separately for individuals with and without intellectual disability in the United States and the United Kingdom.Results
The cost of supporting an individual with an ASD and intellectual disability during his or her lifespan was 2.2 million) in the United Kingdom. The cost of supporting an individual with an ASD without intellectual disability was 1.4 million) in the United Kingdom. The largest cost components for children were special education services and parental productivity loss. During adulthood, residential care or supportive living accommodation and individual productivity loss contributed the highest costs. Medical costs were much higher for adults than for children.Conclusions and Relevance
The substantial direct and indirect economic effect of ASDs emphasizes the need to continue to search for effective interventions that make best use of scarce societal resources. The distribution of economic effect across many different service systems raises questions about coordination of services and sectors. The enormous effect on families also warrants policy attention.
It has been argued that clinical applications of advanced technology may hold promise for addressing impairments associated with autism spectrum disorders. This pilot feasibility study evaluated the application of a novel adaptive robot-mediated system capable of both administering and automatically adjusting joint attention prompts to a small group of preschool children with autism spectrum disorders (n = 6) and a control group (n = 6). Children in both groups spent more time looking at the humanoid robot and were able to achieve a high level of accuracy across trials. However, across groups, children required higher levels of prompting to successfully orient within robot-administered trials. The results highlight both the potential benefits of closed-loop adaptive robotic systems as well as current limitations of existing humanoid-robotic platforms.
In this paper, we propose a therapeutic-assisted robot for children with autism to ameliorate their cof joint attention. The robot conducts a goal-directed based interaction to establish engagement between the child and robot in order to establish a beneficial learning environment for autistic children. An unsupervised Mixture Gaussian-based cluster method is proposed to detect the child's intention in real time to process the goal-directed task smoothly. The novelty of this approach is that does not require the use of any training data or a trained model to detect the child's intention. Our autonomous robotic system is tested with several autistic children at a School for the Disabled in Nagoya, Japan. The results of the initial interaction showed that the children enjoyed interaction with and feedback from the robot, which confirmed that the robot can be used as mediator or an object of joint attention. The unsupervised approach was able to detect the children's intention at every time segment to process the goal-directed task with a higher accuracy rate. The results of the goal-directed task showed that the proposed interaction was highly effective in enhancing their joint attention. Since most of the children attempted to imitate the robot's gestural behaviors and used a variety of learning patterns to attend to the robot's fingered object in the environment to obtain joint attention with robot.
This article describes an exploratory study involving the design of an after-school robotics class for groups of children
at the higher-functioning end of the autistic spectrum. The aim of the study was to foster collaboration among the children
in the context of a class where they programmed Lego robots under the guidance of an experimenter. The class took place once
a week over several months and used many different measures to assess the children’s collaborative behaviours. Detailed analysis
of behavioural data is presented, and despite the small sample size, our findings suggest that the number of potentially collaborative
behaviours the children displayed during a class is more strongly related to the amount of enjoyment the children derived
from the classes than to the number of classes in which the children participated. Parallel-run, free-form drawing sessions
conducted before certain classes gave some indication that these behavioural changes partly generalized to a different context.
Additionally, many of the children in the class either found their experiences in class to be helpful in other social interactions
or expected them to be.
The current study investigated the relationships between internalizing and externalizing (I-E) behaviors and family variables, including both parenting stress and quality of attachment relations, in children aged 8-12 with high-functioning autism spectrum disorder (ASD) or with typical development. Compared to the group with typical development, children with ASD exhibited significantly greater levels of psychopathology as assessed by the Child Behavior Checklist [Achenbach, 1991], and parents of children with ASD exhibited higher parenting stress as assessed by the Parenting Stress Index [Abidin, 1995]. In a hierarchical multiple regression analysis, parenting stress emerged as the most important predictor of children's I-E problems. Results are discussed in light of the two groups' similar relationships between parenting stress and child psychopathology.
Researchers have been placing an increased importance on discovering what variables contribute to better prognosis during behavioral interventions for children with autism. This article preliminarily identifies sleep problems that may exacerbate symptoms of autism; thus, possibly influencing effectiveness of daytime interventions. A data-base of parent report of sleep problems of children with autism (N=55), ranging from 5 to 12 years of age (M=8.2 years) was evaluated. Results suggested that fewer hours of sleep per night predicted overall autism scores and social skills deficits. Similarly, stereotypic behavior was predicted by fewer hours of sleep per night and screaming during the night. Increased sensitivity to environmental stimuli in the bedroom and screaming at night predicted communication problems. Finally, sensitivity to environmental stimuli in the bedroom also predicted fewer developmental sequence disturbances. The results indicate that sleep problems and the diagnostic characteristics of autism may be related. However, future research must be completed to determine the specific relationship.
Autism is a neurodevelopmental disorder with a specific pattern of behavioural, communication and social problems. Additional mental health problems are often poorly understood and undetected. This study investigates the level and pattern of emotional and behavioural problems in young people with autism compared with children with intellectual disability (ID). Subjects were 381 young people with autism and a representative group of 581 Australian young people with ID aged 4-18 years. Parents/carers provided details of the emotional and behavioural problems of their child using the Developmental Behaviour Checklist (DBC-P). Young people with autism were found to suffer from significantly higher levels of psychopathology than young people with ID. The implications of this finding are discussed.
The ability to understand another person's action and, if needed, to imitate that action, is a core component of human social behaviour. Imitation skills have attracted particular attention in the search for the underlying causes of the social difficulties that characterize autism. In recent years, it has been reported that people with autism can bypass some of their social deficits by interacting with robots. However, the robot preference in terms of imitation has yet to be proved. Here we provide empirical evidence that interaction with robots can trigger imitative behaviour in children with autism. We compared a group of high functioning children with autism with a group of typically developing children in a visuomotor priming experiment. Participants were requested to observe either a human or a robotic arm model performing a reach-to-grasp action towards a spherical object. Subsequently, the observers were asked to perform the same action towards the same object. Two 'control' conditions in which participants performed the movement in the presence of either the static human or robot model were also included. Kinematic analysis was conducted on the reach-to-grasp action performed by the observer. Our results show that children with autism were facilitated - as revealed by a faster movement duration and an anticipated peak velocity - when primed by a robotic but not by a human arm movement. The opposite pattern was found for normal children. The present results show that interaction with robots has an effect on visuomotor priming processes. These findings suggest that in children with autism the neural mechanism underlying the coding of observed actions might be tailored to process socially simpler stimuli.
Associations among internalizing, externalizing, and social competence were examined in a longitudinal cohort (N = 205) of 8- to 12-year-old children reassessed after 7, 10, and 20 years. Theoretically informed nested structural equation models tested interconnections among broad multi-informant constructs across four developmental periods. Follow-up analyses examined gender invariance, measurement and age effects, and putative common causes. Key model comparisons indicated robust negative paths from social competence to internalizing problems from childhood to adolescence and from emerging adulthood to young adulthood. Social competence and externalizing problems showed strong initial associations in childhood but no longitudinal cross-domain paths. Using a developmental psychopathology framework, results are discussed in relation to cascade and transactional effects and the interplay between competence and symptoms over time.
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