J. EDUCATIONAL COMPUTING RESEARCH, Vol. 49(3) 381-401, 2013
SOCIAL ROBOTS VS. COMPUTER DISPLAY: DOES THE WAY SOCIAL STORIES ARE DELIVERED MAKE A DIFFERENCE FOR THEIR EFFECTIVENESS ON ASD CHILDREN?* CRISTINA A. POP, RAMONA E. SIMUT, SEBASTIAN PINTEA, JELLE SALDIEN, ALINA S. RUSU, JOHAN VANDERFAEILLIE, DANIEL O. DAVID, DIRK LEFEBER, AND BRAM VANDERBORGHT Babes-Bolyai University
ABSTRACT
Background and Objectives: The aim of this exploratory study is to test whether social stories presented by a social robot have a greater effect than ones presented on a computer display in increasing the independency in expressing social abilities of children with autism spectrum disorders (ASD). Although much progress has been made in developing interventions to improve social skills of children with ASD, a number of unresolved problems still remain. Social robots received increased attention as assisting tools for improving social skills on children with ASD. Methods: Twenty children with ASD (age between 4 and 9 years old) were randomly allocated to three groups: control group (n = 7), computer-presented social stories (n = 6), and robot assisted therapy (n = 7). Results: Overall, our data indicate that using the social robot to implement social story intervention was more effective for improving the independency of expressing social abilities for the participants, than the computer screen. Limitations: Future studies should include a bigger sample size, more intervention sessions, and a follow-up session in order to see if the effect persists in time. Conclusions: The preliminary outcomes of this exploratory research provide empirical bases for further investigations regarding the effectiveness of robot assisted therapy in improving social skills for children with autism through future randomized clinical trials.
*This work was supported by CNCSIS Bucharest, Romania project PN-II-ID-PCE-20113-0484. 381 Ó 2013, Baywood Publishing Co., Inc. doi: http://dx.doi.org/10.2190/EC.49.3.f http://baywood.com
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INTRODUCTION Autism spectrum disorders (ASD) are a spectrum of psychological conditions characterized by widespread abnormalities of social interactions and communication, as well as severely restricted interests and highly repetitive behaviors (American Psychiatric Association, 2000). The most important deficit of children with ASD is considered to be the social impairment (Scattone, 2007). Therefore, many therapeutic tools to improve and to assess the capacity of children with ASD for social interaction and communication are being currently investigated (Moore, McGrath, & Thorpe, 2000; Moore & Taylor, 2000; National Research Council, 2001), but there is still a growing demand for empirical evidence of the effectiveness of these tools. Our main focus will be on social impairments because it is considered to be the most important deficit that individuals with ASD experience across their life span. Simultaneously, it is also the most challenging area for treatment. Social behavior deficits, such as the lack of an awareness of others, the lack of empathy, or poor eye contact, may hinder children diagnosed with ASD from actively participating in simple social play or games (Scattone, 2007). Although behavioral approaches are proven to be effective in reducing ASD symptoms, there is more to be done in this field. More efficient early behavior interventions focused on children are needed in order to facilitate progress at a later stage, ultimately allowing adults to lead almost or entirely autonomous lives. There is, therefore, a critical need for tools capable of increasing the effectiveness of standard intervention techniques. Social Stories Social Stories (SS) are increasingly used as a strategy for improving the social skills of children with ASD (Green, Pituch, Itchon, Choi, O’Reilly, & Sigafoos, 2006). SS are individualized short scenarios that can be used to assist individuals with ASD in describing and understanding social situations (Gray, 2000b). The rationale for using SS for children with ASD is described from the Weak Central Coherence Theory perspective (Happe, 2005), which states that individuals with ASD tend to have a processing style focused on details rather than on the “big picture.” SS includes the important steps that children have to follow in a specific situation, by repeating in different ways specific social elements several times across the story, in order to underline what is important to focus on. Additionally, a meta-analysis of Kokina and Kern (2010) presents how SS components make them an appropriate ASD intervention, by respecting the needs and emphasizing the strengths of children with ASD, such as the need for predictability (American Psychiatric Association, 2000), difficulty in acquiring long response chains (MacDuff, Krantz, & McClannahan, 1993), and preference for visually cued instructions (Quill, 1997).
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Using Computers in ASD Interventions Important advances in computer applications for ASD children have been made over the last 2 decades, which increased technology versatility and reduced financial expense so that computers are now common in schools and children’s homes (Barron, Harmes, & Kemker, 2006; Inan, Lowther, Ross, & Strahl, 2010; Ramdoss, Lang, Mulloy, Franco, O’Reilly, Didden, et al., 2011). There are several advantages of using computer-based intervention for individuals with ASD: computer programs may be created to establish clear routines, reduce distractions, and provide additional control for the influence of autism characteristics (Moore et al., 2000; Silver & Oakes, 2001). Moreover, these interventions allow for the development of their skills in a highly standardized, predictable environment, and therefore enable errors to be avoided, while simultaneously allowing an individual to work at his or her own ability level, offering possibilities to train a wide range of social behaviors (Golan & Baron-Cohen, 2006). These characteristics may be particularly beneficial for the ASD children given that these individuals often experience discomfort with unpredictable social environments (Charlop-Christy, Le, & Freeman, 2000). Computer based interventions (CBI) also encourage children to be an active agent in the education process by directly manipulating and progressing through the intervention programs (Williams, Wright, Callaghan, & Coughlan, 2002). Children with ASD often have relatively strong visual processing skills and a predilection toward electronic media; thus, it is likely that the dissemination of interventions through computers would be particularly appropriate and motivating for these children (Shane & Albert, 2008). Williams et al. (2002) have shown that the learning outcomes of the children in their study (i.e., number of words) were superior when they received the instructions from a computer, compared to the situation when they received instructions from a human instructor. This may be explained by the fact that computers might represent an optimal learning context and allow for the gradual increase of the complexity of the tasks, by solely presenting relevant information. Moreover, a task can be repeated in the same format, without trainer fatigue, offering an appropriate feedback, and children find it intrinsically motivating (Azevedo, & Bernard, 1995; Sansosti & Powell-Smith, 2008). There are a few reviews of the research literature relevant to the use of CBI for children with ASD. Blischak and Schlosser’s (2003) review investigated the use of word processing software with synthetic speech capabilities and found that computer applications using this software is a potential means for improving the spelling and frequency of spontaneous utterances of individuals with ASD. Fitzgerald, Koury, and Mitchem (2008) reviewed reported improvements in academics (i.e., reading, mathematics, writing, social studies, and science) as a result of using CBI by children with mild or high disabilities. Finally, Ramdoss et al. (2011) developed a systematic review of CBI for improving communication
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skills of children with ASD. The results showed that CBI for children with ASD is a promising practice for improving communication skills; however, further investigations regarding the effectiveness of CBI for improving social abilities for children with ASD through randomized clinical trials, both in terms of efficacy (controlled experimental setting) and effectiveness (ecological validity), are needed (David, Lynn, & Ellis, 2010). Robot Assisted Therapy Although CBI (e.g., Ramdoss et al., 2011; Silver & Oakes, 2001) and virtual reality approaches (e.g., Parsons & Mitchell, 2002; Strickland, 1997) have been proven to be useful in ASD therapy, there has been limited investigation of the parameters of the facilitative interactions and the conditions necessary to generalize the benefits to human interactions. Considering this, in order to maximize the potential of the technological tools that may be used in the therapeutic process, new tools for improving the skills of the target population were investigated. Accordingly, social robots were shown to foster more engagement, compliance, trust, and motivation to perform better solely in the context of their physical presence, more than an on-screen agent or a video representation of a robot would (Leyzberg, Spaulding, Toneva, & Scassellati, 2012). The importance of a robot’s embodiment (compared with CBI) was investigated in several studies. Kidd and Breazeal (2004) found that a physically present robot was perceived as more enjoyable and more informative than an on-screen character in a block-moving task. Wainer, Feil-Seifer, Shell, and Mataric (2007) showed that participants rated an embodied robot as more attentive and more helpful than either a video representation of the robot or a simulated on-screen robot-like character. In Bainbridge, Hart, Kim, and Scassellati (2008), a physically-present robot yielded significantly more compliance to its commands than a video representation of the same robot. Tapus, Tapus, and Mataric (2009) found that individuals suffering from cognitive impairment and/or dementia reported being more engaged with a robot assisted treatment than a similar on-screen agent assisted treatment. For more than a decade, a globally diverse set of robotics research groups have examined different robots used for testing the interaction with ASD children (e.g., Diehl, Schmitt, Villano, & Crowell, 2012; Scassellati, Admoni, & Mataric, 2012): humanoid robots like Kaspar (Robins, Amirabdollahian, Ji, & Dautenhahn, 2010), cartoon-like robots such as Keepon (Kozima, Michalowski, & Nakagawa, 2009), robotic dolls like Robota (Billard, 2003), and the IROMEC robot system (Ferrari, Robins, & Dautenhahn, 2009). These studies, presenting a rather qualitative description of the child-robot interaction, showed positive responses of ASD children to robots, based on bigger engagement and higher degree of motivation toward the therapeutic tasks, compared to the interactions with human therapists (Tapus, Peca, Aly, Pop, Jisa, Pintea, 2012). More specifically,
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results show that robots can act as mediators between the child and another person (Pradel & Giannopulu, 2010) and can function as adjuvants in improving social abilities (i.e., play skills) of children with ASD (Ferrari et al., 2009; Francois, Powell, & Dautenhahn, 2009). Exploratory studies from within the robotics and psychology community often show exciting preliminary results, including increased engagement, increased levels of attention, and novel social behaviors such as joint attention and spontaneous imitation, when robots are part of the interaction (Diehl et al., 2012; Ricks & Colton, 2010; Scassellati et al., 2012; Vanderborght, Simut, Saldien, Pop, Rusu, Pintea, et al., 2012). This development comes in the light of research showing that individuals with ASD: (a) are more responsive to feedback, even social feedback, when administered via technology rather than human input (Ozonoff, 1995); and (b) they are more intrinsically interested in treatment when it involves electronic or robotic components (Robins Dautenhahn, & Dubowski, 2006). Our Study A growing number of studies have been investigating the application of advanced interactive technologies in addressing core deficits related to ASD, namely computer technology (Bernard-Opitz, Sriram, & Nakhoda-Sapuan, 2001), virtual reality environments (Parsons & Mitchell, 2002), and robotic systems (Dautenhahn & Werry, 2004; Scassellati, 2005). Also, there are studies that investigated the effects of SS using a multimedia format (i.e., computers) (Hagiwara & Myles, 1999; Sansosti & Powell-Smith, 2008), showing positive effects on specific social communication skills in children with ASD, such as initiating or participating in a preferred play activity or conversation. In accordance to the growing need of techniques for increasing the effectiveness of social skills treatments for ASD children, this exploratory study examines the use of Robot Assisted Therapy (RAT) and its implications in the field of autism treatment. The robot used here is the social robot Probo, which was developed to serve as a multidisciplinary research platform for humanrobot interaction and to develop RAT focused on children (Goris, Saldien, Vanderborght, & Lefeber, 2011). A preliminary exploratory study (Vanderborght et al., 2012) used the social robot Probo as SS telling agent for four pre-schoolers diagnosed with ASD. By using several single case experiments, the authors showed evidence of a higher effectiveness of using Probo rather than a therapist as a story telling agent in improving social abilities in children with ASD. Thus, the children exposed to the social stories told by Probo needed a lower level of prompt from the therapist to perform the target social skills, as compared to the children to whom the social stories were read by the human therapist (Vanderborght et al., 2012).
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Our work incorporates a multi-disciplinary collaboration between psychologists and engineers and provides some enhanced techniques for improving social skills for children with ASD. Moreover, the findings from our research may help teachers to improve their work and to make their intervention easier, by reducing the practitioners’ fatigue. The aim of this exploratory study is to test whether the social robot as a story-telling agent has a greater effect in increasing the independency in expressing social abilities of children with ASD compared to a computer screen playing the same role. More specifically, the social skills targeted in this study were asking questions, eye gaze, asking for help, and greeting. We hypothesize that, as compared to the CBI group, the experimental group will need less prompting from the therapist in performing the target social skills. The second hypothesis is that the children from both groups with interventions will require less prompt than the children from the control group. METHOD Participants Twenty children diagnosed with ASD were randomly assigned in three groups: control group (N = 7), computer-presented SS (SS-PC) (N = 6), and robot assisted therapy (SS-RAT) (N = 7). The participants were randomized using a blocking randomization procedure, with seven blocks with a block size of 3. The children’s chronological age was between 4 and 9 years and they were recruited from two different Romanian autism centers (Autism Transylvania Association and Autism Baia Mare Association). Based on the Children Autism Rating Scale (CARS) (Schopler, Reichler, DeVellis, & Daly, 1980), the participants from each group did not differ on variables like gender, age, or severity of autism. The two intervention groups differed only in the way the social stories were delivered. The inclusion criteria were the following: (a) a current diagnosis of ASD, provided by an outside evaluator using the Autism Diagnostic Observation Schedule–Generic ADOS-G (Lord, Risi, Lambrecht, Cook, Leventhal, DiLavore, et al., 2000) and the criteria outlined in DSM IV-TR (American Psychiatric Association, 2000); (b) lack of social initiations in a given social situation especially created and measured for this study; and (c) ability of recognizing emotions assessed during therapy sessions using the task of facial expression recognition from photographs (Hadwin, Howlin, & Baron-Cohen, 1999). Parents and therapists were interviewed about current strategies used in therapy in order to assure that no other intervention aiming to improve the targeted behaviors was used. All parents were informed and agreed to the participation of their children in this study. This study was approved by the Institutional Review Board of the University.
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Measurements The dependent variable for each participant was the level of prompt needed to provide the expected social response (measured in the experimental task). The prompt can be offered in three different manners: 1. verbal manner (e.g., the therapist provides the first letter from one word or the first word from one sentence); 2. gestural manner (e.g., the therapist indicates with his/her finger, head, or hands specific elements of interest); and 3. physical manner (e.g., the therapist uses gentle movements to direct the child’s head or hands toward specific elements of the therapeutic environment). This variable was assessed using a 7-point scale rating the amount of prompt necessary for a successful social interaction, as follows: 6 = no occurrence of the target behavior even with all kind of prompts; 5 = occurrence of the target behavior with gestural, verbal, and physical prompt; 4 = occurrence of the target behavior with physical and verbal prompt; 3 = occurrence of the target behavior with gestural and physical prompt; 2 = occurrence of the target behavior with verbal prompt; 1 = occurrence of the target behavior with gestural prompt; and 0 = occurrence of the target behavior without any prompt. The 7-point scale was developed taking as a starting point the 5-points scale of Barry and Burlew (2004). The performance of the children was measured in an experimental task that consisted in a structured interaction with the experimenter. Inter-Observer Agreement
Two experienced observers, trained by the experimenters, performed the analyses of video sequences. The individuals who coded the videos were blind observers. An inter-observer agreement was calculated for two observers. The analysis of inter-observer agreement during observation sessions proved a good reliability (Cohen’s kappa higher than 0.8). Treatment Integrity
The trained observers checked also the integrity of treatment implementation for each session and for each participant. A checklist containing the correct procedural steps in implementation was used in order to assess treatment integrity for each session. The mean value of treatment integrity across all session was 89%. The checklist is summarized in Appendix 1.
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Materials Social Stories
The social stories were built based on the steps proposed by Swaggart et al. (1995). First, the target behaviors were identified by applying questionnaires to the participants and their caregivers. The following different abilities were defined by the experimenter in collaboration with the therapist: “Saying Hello,” “Asking questions during playtime,” “Looking in the eyes,” and “Asking for Help.” After this step, the SS were written with care regarding the children’s comprehension level (Gray, 2000b) and included multiple sentences of the four basic types (i.e., descriptive, directive, perspective, and affirmative) (Gray, 2004). For each of the stories, Gray’s guidelines (2004) were respected. SS were visually supported by illustrations appropriate to the child’s reading images skills, attention span, and cognitive ability. The illustrations were selected from the book The New Social Story Book: Illustrated Edition (Gray, 2000a) and they were presented on the robot’s screen (placed in the abdominal region) for the SS-RAT condition or on the PC screen for the SS-PC group. The experimenters participated in a training session regarding SS writing and implementing. SS examples are summarized in Appendix 2.
The Social Robot Probo The social interaction for the social robot Probo was predefined to focus on verbal and non-verbal communication. The robot has a fully actuated head with 20 degrees of freedom capable of showing facial expressions (Saldien, Goris, Vanderborght, Vanderfaeilli, & Lefeber, 2010). The robot is perceived as autonomous by users, but he is always controlled by an operator in a Wizard of Oz setup (Wilson & Rosenberg, 1988), which allows instantaneous adaptation to unexpected behavior/reaction of the participants. With a gamepad and a mouse, the operator is able to make the robot show different emotions, to control the gaze of its head and of the eyes, to start animations (sleeping, nodding yes and no, eyeblink), and to start the preprogrammed SS. A lipsync module allows the lips to move according to the voice, consisting of a pre-recorded neutral male voice. As a prerequisite, the robot operator sat in another room during the whole procedure (see Figure 1). Through the robot’s camera, this allowed the operator to see what was happening in the therapy room and to hear the interactive communication in order to make the appropriate decisions regarding the actions of the robot. The soft touch and huggable appearance of Probo, as well as its capacity to show emotions and use language, make Probo an appropriate tool for an intervention that improves social skills, like SS, with a special focus on ASD children.
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Figure 1. The robot is used in a Wizard of Oz method, with the operator sitting in another part of the room and using a gamepad to control the robot.
Procedure Control Group
The control group did not receive any type of intervention, we only collected data regarding their performance at social abilities targeted in our study, during four observation sessions; each session took place on a different day. Each observation session lasted for about 10 minutes, and each child had to practice the social behavior targeted; a different task was developed for each targeted ability. We investigated the degree of independency of expressing social abilities such as: asking questions, eye gaze, asking for help, and greeting. With a 7-point Likert rating scale we assessed the minimum level of prompt needed for each child to successfully carry out the social exchange. All the observation tasks had a standard format including: number of opportunities, time interval, and toys. The experimental task developed for each of the targeted social behaviors was the same one that was used for all the study conditions. No other interventions were included during this phase. Intervention Groups
Both session types, that is, the sessions where the social stories were delivered on a computer (SS-PC sessions) and those where the social stories were delivered by the social robot (SS-RAT sessions), were conducted by experienced psychotherapists, who were trained by the experimenter and were not aware of the research questions of the study. All the participants from the two intervention groups were exposed to six sessions and followed the same intervention steps: 1. habituation with the robot, assisted by the therapist for the SS-RAT, which lasted for 10-15 minutes; during this phase, Probo was introduced to the
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child by the therapist, then Probo performed some simple actions like saying hello, answering questions with yes or no, saying its name, falling asleep, and singing (in the case of the SS-PC group, the children were already familiar with using computers, so a habituation phase was not necessary; 2. SS listening, in which the social story was told by the robot for the SS-RAT group, or played on a PC screen for the the SS-PC group, both accompanied by visual support; 3. asking the comprehensive questions, which had the purpose of assessing the participants’ understanding of the story (we did not go further with the intervention unless the children answered correctly 100% of the questions); and 4. experimental task, which consisted in exercising the social ability targeted in the SS (see Figure 2). All the sessions were video-recorded for further data analysis. Data Analysis Data were analyzed using SPSS version 16. In order to test if there are differences of performance between Probo, SS-PC, and control group, we used the Kruskal-Wallis test. We chose a non-parametric test for two major reasons: 1. the small sample size for each group (six or seven subjects/group) design that has been used; and 2. non-parametric tests are distribution-free tests. In order to identify the pair of conditions with a significant difference, we used the Mann-Whitney test for each pair of conditions: control group and SS-PC group, control group and SS-RAT, and SS-PC group and Probo group. Another level of interest in our analysis was the effect size level and a qualitative interpretation of the results considering the clinical relevance of the results.
Figure 2. Using the robot Probo as a social story-telling agent.
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RESULTS Statistical Significance Level The results (Figure 3) show an overall significant differences between groups, c2 (2, N = 13), p = 0.047. Using the Mann-Whitney test, we found significant differences only between control group and SS-RAT (U = 7, Z = –2.23, p = 0.025). The results show that there are no significant differences between the control group and the SS-PC group (U = 12.5, Z = –1.21, p = 0.224) or between the SS-RAT and the SS-PC group (U = 10, Z = –1.57, p = 0.116) (see Table 1). Effect Size Level Due to the small number of subjects included in the three conditions, the statistical power of the analysis was a rather low one. Consequently, we computed the effect size for all pairs of conditions, not only for the ones where we found significant differences. The effect size indicator selected was the non-parametrical correlation coefficient phi (j) computed as the square root of chi square (from Kruskal-Wallis), divided by the square root of the number of participants from the
Figure 3. Statistical significance level.
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Table 1. Central Tendency and Dispersion of Help Needed for the Occurrence of the Target Behavior Control
SS-PC
SS-RAT
Mean
2.41
1.65
1.11
Median
2.40
1.62
1.05
Standard deviation
1.05
.56
.43
7
6
7
N
pair of conditions compared (an identical result is obtained by dividing the Z obtained from Mann-Whitney with the square root of the number of participants from the pair of conditions). The phi coefficient ranges from –1 to +1 as the Bravais-Pearson correlation, depicting the intensity of the relationship between the two variables. The results showed a large effect between the SS-RAT and the control group (j = 0.59), a medium effect between the SS-PC group and the control group (j = 0.33) and a medium-to-large effect between the SS-RAT and the SS-PC group (j = 0.43). Clinical Relevance Level We have split the dependent variable into two categories: 1. low level of prompt (including the scores of 0 = occurrence of the target behavior without any prompt and scores of 1 = occurrence of the target behavior with gestural prompt; and 2. high level of prompt (including the scores of 2 = occurrence of the target behavior with gestural prompt, scores of 3 = occurrence of the target behavior with gestural and physical prompt, and the scores of 4 = occurrence of the target behavior with physical and verbal prompt) in order to see the percentage of children who expressed the ability almost independently from each group and the percentage who still needed help to successfully complete the task (see Table 2). The results show that in the control group, 71.4% of the cases needed a high level of prompt and only 28.6% of the cases succeeded in doing the task with a low level of prompt. When it comes to the intervention groups, although the Kruskal-Wallis test shows no significant difference between the SS-RAT and the SS-PC group, the results of the clinical relevance analysis show that 100% of children from SS-RAT did the task with a low level of prompt, compared with the SS-PC group where only 66.7% did. This means that all the children that were in
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Table 2. The Clinical Relevance of Results as a Function of the Level of Prompt Needed for the Occurrence of the Target Behavior Level of prompt needed
Control
SS-PC
SS-RAT
Low degree of prompt
2 (28.6%)
4 (66.7%)
7 (100%)
High degree of prompt
5 (71.4%)
2 (33.3%)
0
(0%)
SS-RAT succeeded in completing the social task almost without any kind of help, while one third of the children from SS-PC group did not succeed in doing the task without any help. Based on these results, the number needed to treat for the social stories delivered by Probo is NNT = 1.4 (the chance that a child will benefit from the treatment is 1 in 1.4), while the number for the social stories in a computer-presented environment is NNT = 2.6 (the chance that a child will benefit from the treatment is 1 in 2.6). CONCLUSIONS Presenting a SS intervention with the help of the social robot Probo showed positive effect in increasing the independency in expressing social abilities of children with ASD. This exploratory study expands the current body of research in the area of interventions for improving social skills of children with ASD by: (a) incorporating the use of technology (social robots) to implement an intervention technique in therapy; and (b) evaluating the effectiveness of RAT in comparison both with control group and the computer-based technique. Statistical Significance Level When comparing the performance of the participants from the three groups through non-parametric tests, we found no significant difference in neither the performance of the participants from the two groups with intervention (SS-PC and SS-RAT), nor between the participants from control group and the SS-PC group. We found significant differences only between control group and SS-RAT, which means that we can consider Probo to be an effective agent of social story telling. Effect Size Level Following the intervention of SS in RAT sessions, participants demonstrated improved rates of independency in expressing targeted social communication behaviors compared to the performance of the control group. Moreover, when we take into account the results from the effect size level analysis, there is significant difference between the two interventions in favor of SS-RAT. The results also
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showed a large effect between the SS-RAT and the control group and a medium effect between the SS-PC group and the control group. Clinical Relevance Level An analysis of the level of prompt provided for the children from every group shows that 100% of the children from SS-RAT needed the minimum level of prompt or they did the social task independently, compared with SS-PC group were only 66 (7%) did the task with a low level of prompt; these results show that Probo can help children with ASD to independently express their abilities and improve their social interaction with others. There could be two types of possible explanation for the fact that we found no significant statistical difference in the performance of the participants from the two groups with intervention. First, considering that the direction of the results is according to the expected direction (SS-RAT better than SS-PC), a higher statistical power of the analysis (a larger sample for each condition), with similar results could confirm our hypothesis from a statistical point of view. Second, from the procedural point of view, the position of the robot during the sessions for the SS-RAT might represent a variable that can explain the fact that the effectiveness of the two interventions is similar, and there is no significant difference between SS-PC and SS-RAT. Due to the fact that Probo (80 cm length) was standing up on a small table, the children that were sitting down in front of it could not see the entire robot without switching their attention from its abdomen to the other body parts of the robot (e.g., mouth). In the current literature, the shifting attention ability/eye gaze alternation is presented as a prerequisite necessary to complete a social task and it can interfere with the performance from our task (Jones, Carr, & Feeley, 2006). Moreover, taking into account the general declared preference of ASD children for computers (Bernard-Opitz, Ross, & Tuttas, 1990; Moore & Calvert, 2000), the PC screen can be considered a favorite or ritualistic object for the child. This can increase the difficulty of switching the attention from the abdominal screen back to the robot’s face or more than that, to hinder the eye gaze alternation process. Despite the fact that we found no statistically significant differences between SS-PC and SS-RAT, the effect size analysis and clinical relevance level represent empirical evidence that using social robots in therapy for children with ASD may increase the independency of expressing social abilities more than just using a computer screen. DISCUSSION In the presented work we focused on testing whether SS presented by a social robot has a greater effect than presented on a computer display in increasing the independency in expressing social abilities of children with ASD. The analysis
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of our data indicate that SS interventions delivered with the help of the social robot Probo showed positive effect in increasing the independency in expressing social abilities of children with ASD. These preliminary outcomes of this exploratory research provide empirical bases for further investigations regarding the effectiveness of robot assisted therapy in improving social skills for children with autism through future randomized clinical trials. As a conclusion we may say that our findings can be added to the amount of studies that highlight the idea that robots can be a component of intervention for children with ASD; they can mediate the interaction between child and the human therapist. However, future studies should include a bigger sample size, more intervention sessions, and a follow-up session in order to see if the effect persists in time (these issues can be also considered as limits of our current study). The age range (between 4 and 9 years old) can be considered another limit of our study, since the development of social skills can vary a lot through this age interval, so future studies should consider narrowing down the age interval. Our future work should also focus on other types of techniques that can be improved by their use during RAT sessions, in order to help therapists overcome the difficulties that they have in enhancing some abilities of children with ASD. Based upon these promising results obtained mainly at the size effect and clinical relevance levels, this line of studies offers great opportunities for both practitioners and caregivers of children with ASD. The use of social robots, such as Probo, might offer a higher degree of interactivity and, also, due to the ability of the robot to express emotions associated to each social story, the children have better chances to generalize these emotions to real life situations than by being exposed to computer screens. In order to have a clearer idea about the effectiveness of how social robots may improve the abilities of children with ASD, more clinical trials (both efficacy and effectiveness studies) are needed. However, the collaboration between the two fields—engineering and psychology—is quite difficult because of the differences in work that they focus on (Kim, Paul, Shic, & Scassellati, 2012). For example, although the design of the robots has received considerable attention, there is still a gap between the needs of the special populations and the characteristics of the robots which are not specially designed in order to meet the psychological needs of the targeted population.
APPENDIX 1: Checklist QA: Please check wording (write down “what”?)
Please write down __ when you consider that the answer is YES, near the number that corresponds to the intervention step that was respected by the experimenter, and O when you consider that the intervention step was not respected. In the column named OBSERVATIONS you are free to argue your answer (optionally, just if the situation is not clear enough to give a clear answer).
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1. Triggering the beginning of the social story (using verbal expressions like: “The story starts now”/“Let’s listen the story”/“Pay attention, the story starts”). 2. Assure that the participant has all the necessary conditions in order to pay attention/to follow the story (has the correct body position, it is oriented to the robot or PC) the therapist stopped the story when the child could not focus his attention to the story or that he/she offered verbal prompts (“are you paying attention to the story”), indicative prompts (pointing with the index finger to the device) or a physical prompt (slowly orientation of the child’s head to the device). 3. Asking the three comprehensive questions immediately after the story ends (the comprehensive questions are specific for each story). 4. Creating the work task by giving the required clues to the participant from the story. 5. Implementation of the task clues in a natural and proper common life environment (if the situations that are created to express the targeted behaviors through the story can be found in the daily life of the child). 6. Offering help to the child by supplying the right answers (if the experimenter offers a prompt when the child cannot independently give the right answer). 7. Offering feedback to the participant (in order to correct the wrong answers or to give a reward for the correct answer). APPENDIX 2. “Saying Hello” Story Hello! My name is Probo. When I see someone I say hello.
I can say hello more than once a day. I can say hello to my mother when I wake up in the morning.
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I can say hello to my friends and my teacher when I go to kindergarden. I can say hello to the people I just met.
People are happy when I say hello. J
When I meet someone and I don’t say hello they can get upset. L
When I say hello to someone I look that person in the eye.
It’s nice to say hello when I meet someone.
ACKNOWLEDGMENTS The authors especially thank the children and their families for involving in our study and the therapy centers from Romania, Autism Transylvania Association, and Autism Baia Mare, for the hospitality to perform the experiments.
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