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Dubois-Sage, M.; Jacquet, B.; Jamet, F.; Baratgin, J. Interacting with a Robot for Individuals with ASD. Encyclopedia. Available online: https://encyclopedia.pub/entry/55464 (accessed on 19 April 2024).
Dubois-Sage M, Jacquet B, Jamet F, Baratgin J. Interacting with a Robot for Individuals with ASD. Encyclopedia. Available at: https://encyclopedia.pub/entry/55464. Accessed April 19, 2024.
Dubois-Sage, Marion, Baptiste Jacquet, Frank Jamet, Jean Baratgin. "Interacting with a Robot for Individuals with ASD" Encyclopedia, https://encyclopedia.pub/entry/55464 (accessed April 19, 2024).
Dubois-Sage, M., Jacquet, B., Jamet, F., & Baratgin, J. (2024, February 26). Interacting with a Robot for Individuals with ASD. In Encyclopedia. https://encyclopedia.pub/entry/55464
Dubois-Sage, Marion, et al. "Interacting with a Robot for Individuals with ASD." Encyclopedia. Web. 26 February, 2024.
Interacting with a Robot for Individuals with ASD
Edit
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. The benefits of robots and the reasons put forward to explain these results will be looked at by researchers. 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.
autism spectrum disorder socially assistive robot human–robot interaction social skills social motivation social cognition

1. Introduction

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by deficits in communication and social interaction as well as restricted or repetitive patterns of behavior, interests, or activities. A neurobiological dysfunction is thought to be at the root of this disorder. Symptoms appear early in development and have a major impact on the child’s daily life in many contexts, particularly in situations of social interaction. Robotics, a currently expanding field, could be of great interest in improving support for specific populations and in particular individuals with ASD. Robots can be categorized according to the different functions they perform. Examples include social robots, which specialize in interacting with humans through gestures and speech, and assistance robots, which aim to help people with special needs. The use of robots has recently expanded into a new field of application: socially assistive robots, which aim specifically to foster engagement in social interactions with specific populations.
According to the DSM-5 classification, the two main criteria for autism are impaired communication and social interaction on the one hand and restricted interests and repetitive behaviors on the other [1]. A review of the literature shows that robots can address both symptoms: their use with autistic people is generally aimed at improving communication skills and reducing repetitive behaviors [2]. Thus, interventions are particularly geared towards communication and social interaction difficulties but also focus on more specific behaviors, such as learning appropriate behaviors and reducing maladaptive behaviors (stereotyped behaviors and anxiety).
To determine the benefits of robots for individuals with ASD, researchers first conducted a search on Google Scholar using the following keywords: “autism + robot + benefits”, yielding 24,900 results. As this research is not intended to be systematic, researchers were particularly interested in experimental papers dealing with the progress observed in individuals with ASD following interaction with a robot (see [3] for a systematic review). Researchers have excluded experimental papers dealing with the use of virtual robots, focusing on the use of robots in an interactive setting. In all, researchers selected 50 experimental studies, with publication years ranging from 2008 to 2023.
Three types of interventions can be distinguished according to the objective sought [4]: robots can promote communication and social interaction [5][6][7][8], supporting the learning of specific behaviors, such as emotion recognition [9][10], and reducing the frequency of behaviors deemed maladaptive, including repetitive behaviors and anxiety [11].

2. Fostering Communication and Social Interaction

Social assistance robots have positive effects on the social abilities of children with ASD, who generally show more social behaviors during interaction with a robot than with a human [7][12]. This benefit can be observed across a range of social behaviors impacted by ASD: eye contact, joint attention, collaborative play and activity engagement skills, touch, verbal communication, and imitation. Reseachers will list the effects of a robot for each of these behaviors (see Table 1 for a summary).
Table 1. Benefits of robots in fostering communication and social interaction in individuals with ASD.
Section Article Variable Effect Effect p-Value Robot Sample Size (ASD) Mean Age (Standard Deviation) Functioning/Mean IQ (Standard Deviation) Duration of Robot Intervention (mn) Country
Eye contact Barnes et al. [13] Eye gaze robot > human NA NAO 3 8.33 (4.04) NA 1 session (NA) USA
  Bekele et al. [14] Eye gaze robot > human 𝑝<0.05 NAO 6 2.78–4.9 y.o. NA 1 session (30–50 mn) USA
  Cao et al. [15] Eye gaze robot > human 𝑝<0.05 NAO 15 4.96 (1.10) NA 1 session (NA) China
  Costa et al. [16] Eye contact robot > human 𝑝<0.001 KASPAR 8 6–10 y.o. NA 7 sessions (NA) UK
  Costa et al. [17] Eye gaze robot > human 𝑝<0.05 QTRobot 15 9.73 (3.38) IQ < 80 (n = 8); 80–120 (n = 6); IQ > 120 (n = 1) 1 session (1.5–4.3 mn) Luxembourg
  Damm et al. [18] Eye gaze robot > human 𝑝<0.05 FLOBI 9 21 (NA) 112.5 (range: 94–133) NA Germany
  David et al. [19] Eye contact robot > human for 2/5 children 𝑝=0.01 NAO 5 3–5 y.o. LF-HF 8–12 sessions (10 mn/session, 1/day) Romania
  Duquette et al. [20] Eye contact robot > human 𝛽=0.35 TITO 4 5.1 (NA) LF 3/week for 7 weeks (NA) Canada
  Scassellati et al. [8] Eye contact with other people pretest < post-test 𝑝<0.01; 𝑝<0.05 JIBO 12 9.02 (1.41) IQ ≥ 70 23 sessions (30 mn/session, 1/day) USA
  Shamsuddin et al. [21] Eye contact robot > human NA NAO 1 10 y.o. 107 1 session (15 mn/session) Malaysia
  Simlesa et al. [7] Eye contact robot > human 𝑝<0.05 NAO 12 5.2 (0.63) MA: 2–3 y.o. 1 session (NA) Croatia
  Simut et al. [22] Eye contact robot > human 𝑝<0.05 PROBO 30 6.67 (0.92) 91.23 (range: 70–119) 1 session (15 mn/session) Belgium
  Tapus et al. [23] Eye gaze robot > human 𝑝<0.05 NAO 4 4.2 (1.67) NA 7–13 sessions (8 mn/session, 2/day) Romania
  Wainer et al. [24] Eye contact robot > human 𝑝<0.05 KASPAR 6 6–8 y.o. NA 2 sessions (15 mn/session) UK
Joint attention Anzalone et al. [25] Joint attention robot < human 𝑝<0.01 NAO 16 9.25 (1.87) 73 (14) 1 session (NA) France
  Cao et al. [15] Joint attention robot = human 𝑝>0.05 NAO 15 4.96 (1.10) NA 1 session (NA) China
  Cao et al. [26] Joint attention robot < human 𝑝<0.001 NAO 27 46.37 months (4.36) MA: 42 months max 2 session (NA) The Netherlands
  Ghiglino et al. [6] Joint attention robot = human 𝑝>0.05 Cozmo 24 5.79 (1.02) 58.08 (19.39) 5 weeks (10 mn/session) Italy
  Kajopoulos et al. [27] Joint attention pretest < post-test 𝑝<0.05 CuDDler 7 4–5 y.o. NA 6 sessions over 3 weeks (20 mn/session) Singapore
  Kumazaki et al. [28] Joint attention time +; robot > human 𝑝<0.01 CommU 28 70.56 months (6.09) (robot group); 69.00 (4.39) (control) NA 1 session (15 mn) Japan
  So et al. [29] Joint attention pretest < post-test (robot) 𝑝<0.05 HUMANE 38 7.51 (0.87) (robot group); 7.91 (0.89) (human group) LF 6 sessions (30 mn/session) China
  Taheri et al. [30] Joint attention time + 𝑝<0.05 NAO/ALICE-R50 6 6–15 y.o. LF-HF 12 sessions over 3 months (30 mn/session) Iran
  Warren et al. [31] Joint attention time + 𝑝<0.01 NAO 6 3.46 (0.73) NA 4 sessions over 2 weeks (NA) USA
  Wiese et al. [32] Gaze cueing effect robot > human 𝑝<0.01 EDDIE 18 19.67 (1.5) NA 1 session (15 mn) Germany
Interaction Ghiglino et al. [6] Social interaction initiation robot > human 𝑝<0.05 Cozmo 24 5.79 (1.02) 58.08 (19.39) 5 weeks (10 mn/session) Italy
  Kim et al. [33] Social behaviors towards peer robot > human 𝑝<0.05 PLEO 24 4–12 y.o. NA NA USA
  Pop et al. [34] Collaborative game robot > human 𝑝<0.05 PROBO 11 4–7 y.o. IQ >70 8 sessions (1 mn/session) Romania
  Pliasa et al. [35] Social interaction initiation robot > human 𝑝<0.05 DAISY 6 6–9 y.o. NA 2 sessions (20 mn/session) Bulgaria
  Rakhymbayeva et al. [36] Engagement time tendency time 2 > time 1; familiar > unfamiliar activities 𝑝=0.05; 𝑝<0.05 NAO 7 6.1 (2.7) LF 7–10 sessions (15 mn/session) Khazakstan
  Stanton et al. [37] Social interaction initiation robot > human 𝑝<0.05 AIBO 11 5–8 y.o. NA 1 session (30 mn) USA
  Wainer et al. [24] Cooperation in game robot > human 𝑝<0.01 KASPAR 6 6–8 y.o. NA 2 sessions (15 mn/session) UK
Touch Costa et al. [16] Spontaneous touch robot > human NA KASPAR 8 6–10 y.o. NA 7 sessions (NA) UK
  Simlesa et al. [7] Touch robot > human 𝑝<0.05 NAO 12 5.2 (0.63) MA: 2–3 y.o. 1 session (NA) Croatia
Communication Farhan et al. [38] Verbal and non-verbal communication time 4 > time 1 NA NAO 4 5, 12, 13, 24 y.o. range: 41–47 4 sessions (NA) Bangladesh
  Huskens et al. [5] Self initiated questions pretest < post-test; robot = human 𝑝<0.05; 𝑝>0.05 NAO 6 3-14 y.o. IQ >80 4 sessions (10 mn/session) Netherlands
  Kim et al. [33] Speech robot > human 𝑝<0.05 PLEO 24 4–12 y.o. NA NA USA
  Kumazaki et al. [39] Posture, gaze, facial expressions robot > human 𝑝<0.001 ACTROID-F 29 29.1 (2.6) IQ ≥ 70 1 session (25 mn) Japan
  Simlesa et al. [7] Vocalization robot < human 𝑝<0.01 NAO 12 5.2 (0.63) MA: 2–3 y.o. 1 session (NA) Croatia
  Stanton et al. [37] Speech robot > human 𝑝<0.05 AIBO 11 5–8 y.o. NA 1 session (30 mn) USA
  Syrdal et al. [40] Communication number of interactions + 𝑝<0.05 KASPAR 19 2–6 y.o. NA NA UK
  Taheri et al. [30] Verbal communication time + 𝑝<0.05 NAO/ALICE-R50 6 6–15 y.o. LF-HF 12 sessions over 3 months (30 mn/session) Iran
Imitation Conti et al. [41] Imitation time + NA NAO 6 5 and 10 y.o. LF 15 sessions (6–8 mn/session) Italy
  Costa et al. [17] Imitation robot = human 𝑝>0.05 QTRobot 15 9.73 (3.38) IQ < 80 (n = 8); 80–120 (n = 6); IQ > 120 (n = 1) 1 session (1.5–4.3 mn) Luxembourg
  Duquette et al. [20] Imitation of facial expressions; of words and gestures robot > human; robot < human NA TITO 4 5.1 (NA) LF 3/week for 7 weeks (NA) Canada
  Pierno et al. [42] Imitation velocity robot > human 𝑝<0.001 ROBOTIC ARM 12 11.1 (NA) HF 1 session (NA) Italy
  Simlesa et al. [7] Imitation robot = human 𝑝>0.05 NAO 12 5.2 (0.63) MA: 2–3 y.o. 1 session (NA) Croatia
  Soares et al. [43] Imitation of emotions robot > human; post-test > pretest (robot), post-test = pretest (human) 𝑝<0.05; 𝑝<0.05; 𝑝>0.05 Zeno 45 6.8 (1.5) (robot group); 7.5 (1.4) (human group); 7.8 (1.2) (control) HF 2/week for 3 weeks (5–15 mn/session) Portugal
  Taheri et al. [44] Imitation robot < human 𝑝<0.001 NAO 20 4.95 (2.01) NA 1 session (NA) Iran
  Zheng et al. [45] Imitation quality robot > human 𝑝<0.05 NAO 6 3.83 (0.54) NA 2 sessions (NA) USA
HF: High-Functioning Autism; IQ: Intellectual Quotient; LF: Low-Functioning Autism; MA: Mental Age; NA: Not Available; y.o.: Years Old.

3. Fostering Specific Behaviors

The application of social robots with autistic individuals can also target the improvement of a particular behavior. The work presented in this section is of two types. Some studies promote the emergence of relevant and appropriate behaviors, while others aim to reduce maladaptive behaviors (stereotyped or repetitive behaviors) and anxiety. Researchers will examine the benefits of a robot on these behaviors (see Table 2 for a summary).
Table 2. Benefits of robots in fostering specific behaviors in individuals with ASD.
Section Article Variable Effect Effect p-Value Robot Sample Size (ASD) Mean Age (Standard Deviation) Functioning/Mean IQ (Standard Deviation) Duration of Robot Intervention (mn) Country
Appropriate behaviors Bharatharaj et al. [46] Touching interaction NA NA KiliRo 24 9.71 (3.24) NA 1/day for 7 weeks (60 mn/session) India
  Costa et al. [16] Appropriate touch gentle touch > harsh 𝑝<0.05 KASPAR 8 6–10 y.o. NA 7 sessions (NA) UK
  David et al. [19] Turn-taking skills robot = human for 3 children 𝑝>0.05 NAO 5 3–5 y.o. LF-HF 8–12 sessions (10 mn/session, 1/day) Romania
  Ghiglino et al. [47] Theory of Mind skills training with humanoid robot > non-anthropomorphic robot and traditional therapy 𝑝<0.001; 𝑝<0.01 iCub, COZMO 43 5.8 (1.14) 71.48 (16.50) (COZMO); 71.14 (15.49) (iCub) 2/week for 8 weeks (15 mn/session) Italy
  Holeva et al. [48] Theory of Mind skills (NEPSY II) robot training = human; pretest < post-test 𝑝>0.05; 𝑝<0.001 NAO 44 9.48 (1.95) IQ > 70 2/week for 3 months (NA) Greece
  Lakatos et al. [49] Visual Perspective Taking and Theory of Mind skills (Charlie test) pretest < post-test 𝑝<0.05 KASPAR 13 8.11 (1.96) 79.30 (14.33); range: 60–103 1 to 10 sessions (15–20 mn/session) UK
  Lee et al. [50] Proper force of touching feedback > no feedback 𝑝<0.05 Touch pad 1 22 y.o. 49 1 session (NA) Japan
  Marino et al. [10] Recognition and understanding of emotions pretest < post-test (robot training); pretest = post-test (human training) 𝑝=0.001; 𝑝>0.05 NAO 14 73.3 months (16.1) (robot group); 82.1 (12.4) (human) NA 10 sessions (90 mn/session, 2/week) Italy
  So et al. [51] Recognition and production of intransitive gestures robot training > no training 𝑝<0.05 NAO 30 5.10 (0.83) (experimental group); 5.8 (0.35) (control) NA 4 sessions (30 mn/session, 2/week) China
  So et al. [9] Recognition and production of emotional gestures robot training > no training 𝑝<0.001 NAO 13 8.99 (2.14) (experimental group); 9.50 (2.42) (control) range: 49–67 4 sessions (30 mn/session, 2/week) China
  So et al. [52] Recognition and production of intransitive gestures robot training = human 𝑝>0.05 NAO 23 9.17 (1.29) (robot group); 8.92 (0.93) (human) range: 46–74 5 sessions (30 mn/session, 2/week) China
  Takata et al. [53] Understanding of others’ feelings and behaviors pretest < post-test 𝑝<0.01 Sota, CommU, A-Lab android ST 14 17.57 (3.39) 89.50 (10.95) 5 sessions (1 h/session, 1/day) Japan
  Wood et al. [54] Theory of Mind skills (Charlie test) pretest < post-test for 7/12 children 𝑝<0.05 KASPAR 12 11–14 y.o. MA: 6–14 y.o. 2–10 sessions (NA) UK
Reducing maladaptive behaviors Bharatharaj et al. [46] Stress level pretest > post-test 𝑝<0.05 KiliRo 24 9.71 (3.24) NA 1/day for 7 weeks (60 mn/session) India
  Costa et al. [17] Stereotyped behaviors robot < human 𝑝<0.05 QTRobot 15 9.73 (3.38) IQ < 80 (n = 8); 80–120 (n = 6); IQ > 120 (n = 1) 1 session (1.5–4.3 mn) Luxembourg
  Kumazaki et al. [39] Stress level robot < human 𝑝<0.01 ACTROID-F 29 29.1 (2.6) IQ ≥ 70 1 session (25 mn) Japan
  Pop et al. [34] Stereotyped behaviors robot < human 𝑝<0.05 PROBO 11 4–7 y.o. IQ > 70 8 sessions (1 mn/session) Romania
  Shamsuddin et al. [21] Stereotyped behaviors robot < human NA NAO 1 10 y.o. IQ = 107 1 session (15 mn) Malaysia
  Shamsuddin et al. [11] Stereotyped behaviors robot < human NA NAO 6 8.9 (NA) range: 46–78 5 sessions (15 mn/session) Malaysia
  Stanton et al. [37] Stereotyped behaviors robot < toy 𝑝=0.06 AIBO 11 5–8 y.o. NA 1 session (30 mn) USA
HF: High-Functioning Autism; IQ: Intellectual Quotient; LF: Low-Functioning Autism; MA: Mental Age; NA: Not Available; y.o.: Years Old.

3.1. Supporting the Learning of Appropriate Behaviors

Interactions with robots offer the possibility of designing specific remediation to support particular learning, such as learning turn-taking [19][55] or non-verbal language gestures [9][51], emotion recognition [10], or regulating touch and physical contact [16].
In addition to using robots to increase the occurrence of certain behaviors, other protocols use robots to reduce the occurrence of maladaptive behaviors.

3.2. Reducing Maladaptive Behaviors: Repetitive Behaviors and Anxiety

The use of the NAO robot could reduce the percentage of stereotyped behaviors in children aged 5 to 13 [11][21]. In other studies, children also show fewer stereotyped behaviors when performing an activity with a robot partner than with a human partner [17][34]. The frequency of autistic behavior tended to decrease when children interacted with an AIBO dog robot rather than a mechanical dog toy [37]. In addition, using a KILIRO parrot robot for 60 min a week for 7 weeks helps both children and adolescents (aged 6–16) to reduce their stress levels [46]. In adults with ASD, the stress reduction observed during job interview training was greater for training with an android robot than with a human [39], suggesting that interacting with a robot is less stressful than interacting with a human for individuals with ASD. It is worth noting that the most anxious children display more stereotyped behaviors [56]. Stress levels could be linked to the occurrence of global and motor stereotyped behaviors (but not to verbal stereotyped behaviors) [57]. Reducing the stress involved in interacting with a human by using a robot as a partner could therefore help to reduce stereotyped behaviors in individuals with ASD.
In this way, socially assistive robots can promote communication and social interaction in autistic children, support specific social learning, and reduce repetitive behaviors. However, the results are mixed when researchers compare the effectiveness of training with a robot with that of training with a human. While some studies show that robots are more effective than humans (e.g., [6][7][13][19][45][47]), others show that they are comparable (e.g., [5][17][48]) or even less effective [25][26] than humans. This heterogeneity in results can be partly explained by the wide variety of skills targeted by robot intervention. A meta-analysis confirms the benefits of robots on the social development of children with ASD, but not on motor or emotional aspects [3].

4. A Preference for Interacting with Robots Rather than Humans in Individuals
with Autism Spectrum Disorder?

The benefits for individuals with ASD of interacting with a robot (at least in terms of social development) raise several questions. First, it is worth asking whether this type of interaction is more attractive to individuals with ASD than interaction with a human, as has been proposed in several studies [7][47][58][59]. In the next section, researchers will look at how individuals with ASD perceive robots, and what characteristics they attribute to them.

5. Reasons Provided to Explain the Benefits of Robots

Several explanations can be proposed based on different theories aimed at explaining the social difficulties observed in autism. Researchers have already observed that people with ASD have social difficulties and show less interest in social stimuli than Typically Developing (TD) individuals. The link between social skills and social motivation seems well established in children with ASD: those with the least social motivation have more severe social difficulties [60][61][62]. Nevertheless, the meaning of this association remains to be determined.

Two main theories have been proposed to explain the association between social difficulties and reduced social interest observed in autism [63]: Social Motivation Theory [64] and Social Cognition Theory [65][66]. Researchers will analyze the two theories that seek to explain the causality between these two characteristics of ASD and build on these theories to explain the benefits brought about by robots. 

6. Conclusions

In conclusion, the use of robots with people with ASD appears to be beneficial in encouraging communication and social interaction, supporting the learning of specific social behaviors, and reducing maladaptive behaviors. Interaction with robots could improve the social skills of individuals with ASD [3]. Children with autism touch and look more at a robot than at a human [7][17][19]. They also show a greater tendency to follow a robot’s gaze than a human’s gaze [32]. Children’s participation in an activity is increased when a robot is present [34][36], thus increasing interaction initiation [6][35] and speech production [33]. During an action imitation task performed by a human or robotic arm, children with autism perform better with the robotic arm, while TD children perform better with the human arm [42]. Furthermore, when ToM training is implemented, children with ASD make more progress with a humanoid robot than with a human [47], and the same results are observable in emotion recognition training with an iconic robot [10]. Finally, studies suggest that the stress felt by individuals with ASD during social interactions could be reduced with a robotic partner [39], leading to a decrease in the occurrence of stereotyped behaviors [17][34]. Further studies are needed to confirm the influence of robots on stereotyped behavior, but the benefits of robots on social development have been confirmed by a recent meta-analysis [3].

Although autistic children may categorize robots in the same way as TD children, they seem more attracted to robots and attribute more human characteristics to them. Some studies even suggest that theyare more interested in robots than in humans. Researchers sought to explain the benefits of robots by drawing on two theories: Social Motivation Theory and Social Cognition Theory. On the one hand, considering Social Motivation Theory, individuals with ASD may show more interest in a non-human agent than in a human one. This increased interest in interaction would then allow them to accumulate social experience, which could consequently reduce their social difficulties. On the other hand, as Social Cognition Theory argues that people with ASD engage less in interactions due to difficulties in understanding the social world, it is conceivable that a simpler, more predictable agent such as a robot could reduce these difficulties. As a result, this type of agent would encourage autistic individuals to engage more fully in social interactions. The robot, as a more attractive, simplified, and predictable social agent than a human, would thus encourage social interactions in autistic individuals. For children with significant social difficulties, robot-assisted training could thus constitute a step of intermediate difficulty compared to training with a human [67].

It therefore seems appropriate to rely on this type of agent when assessing the social skills of individuals with ASD: by reducing the difficulty of the interaction, a robot could enable children to better mobilize their abilities, leading to better estimation of their social skills. This suggests that psychology tests might be more successful if the experimenter is a robot rather than a human, as has already been shown in TD children [68][69][70][71][72]. The robot would then provide a more accurate means of assessing social–cognitive functioning [73][74], which would be particularly relevant for children with ASD [75].

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