Children on the Autism Spectrum and the Use of Virtual Reality for Supporting Social Skills

Abstract

Background: Autism spectrum disorders (ASDs) are characterized by differences in socio-pragmatic communication. These conditions are allocated within a “spectrum” of phenotypic variability. Virtual reality (VR) is a useful tool for healthcare intervention and particularly safely advancing social abilities in children with ASD. Methods: In our study two types of intervention for improving social skills were compared: (i) emotional training obtained by the use of virtual reality (Gr1), (ii) traditional emotional training performed individually with a therapist (Gr2). We aimed to identify the intervention with the shortest acquisition time for the proposed social tasks. Results: Our findings show that both types of intervention had the same acquisition time for the recognition of primary emotions. However, for the use of primary and secondary emotions, the group using VR showed shorter acquisition times. Conclusions: These findings together with previous preliminary datasuggest that VR can be a promising, dynamic and effective practice for the support of basic and complex social skills of these individuals.

1. Introduction

Disorders of the autism spectrum (ASDs) are described as pervasive, chronic and persistent neuro-developmental conditions affecting approximately 1 in 68 children [1,2]. This condition is characterized by fundamental difficulties in socio-emotional reciprocity, interpersonal connection and a repertoire of restricted and monotonous interests and behaviors [3,4,5]. The previous diagnostic manual, DSM-IV-TR [6], divided autism-spectrum-affected individuals into five subcategories, including individuals with Asperger’s syndrome (AS). In the new diagnostic manual, DSM5 [3], this subdivision has been removed and replaced with a severity level value (1 corresponding to mild symptoms, 2 to moderate and 3 to severe). We therefore consider a single ASD category which groups a continuum of clinical conditions into one spectrum, rather than considering those behaviors distinct and separated into specific subcategories. In the present manuscript we use the terms “autism” and “on the autism spectrum”, as well as “autism spectrum disorder” (ASD), as they are preferred by the community [7]. Individuals on the autism spectrum often feel social motivation; however, there is a need for assistance in forming relationships since their relational modalities appear one-sided [8]. Moreover, they present a high IQ compared to peers. Regarding communication, individuals on the autism spectrum implement a formally correct language; however, their pragmatic skills need to be reinforced. To do so, it may be useful and effective to practice interventions for the support of social skills using protocols that can improve their interactions and, in general, their daily lives [9]. A few studies demonstrated that individuals with ASD can learn to act in social situations if they have the opportunity to regularly participate in specific scenarios [10,11,12]. Studies have shown that traditional educational interventions for individuals with ASD can be expensive, inaccessible and inefficient as a result of limited resources and a faint motivational index [13,14]. In recent years, virtual reality (VR)-based interventions demonstrated potential because of their low cost, a high motivational index for individuals with ASD, and their relatively vast access [15,16,17,18,19]. The majority of children with ASD show familiarity with information technology, leading them to have a higher level of involvement and a reduction in problem behaviors in virtual interactions [13,20]. In particular, VR technologies let children with ASD actively be part of interactive and captivating situations (virtual reality intervention—VRI) [21,22]. Several VR-based systems were developed to teach important life skills, e.g., driving skills [23] and social skills to individuals with ASD, and data imply that such individuals were capable of apprehending, using and reacting appropriately to virtual environments and have the possibility to transfer these skills into real life [15,19,24,25,26]. Recent studies have highlighted the validity of VR within the treatment options for individuals with level 1 ASD [3,6,27,28,29]. Modern research has highlighted the importance of using VR interventions such as computer aided reality simulations in which individuals with HFA can practice arduous or individually challenging social interactions [30,31,32,33]. Several researchers have focused on the intervention for emotions [34,35,36,37], but they have mainly used avatars or learning games for the identification of basic emotions [34], the regulation of emotional expression and social emotional reciprocity [36,37].

Our idea is that VR interventions can lead to a faster and more stable acquisition of social skills over time. In a previous study [38] we have already validated our idea by investigating how VR had facilitated an improvement in social skills for individuals with HFA in a faster way than simple emotional literacy training as the subject has direct experience of social situations and has a way of experiencing emotions immersed in the context itself (and not looking at it from the outside as in traditional training).

In this study we expanded our study sample and compared two types of intervention methods for the enhancement of social skills. The first method is a traditional emotional literacy intervention [39] carried out in an individual relationship with the therapist [40]. The second method is an emotional literacy intervention structured through the use of VR [37,39]. The emotional literacy intervention can improve the ability to recognize and label emotions, and in this study we also associated it with work on the ability to match primary and secondary emotions to situations. In both cases the intervention, aimed at individuals with ASD, proposed four social tasks: (a) recognition of primary or basic emotions (PE), (b) recognition of secondary emotions (SE), (c) emotions and situations for primary emotions (ESPE) and (d) emotions and situations for secondary emotions (ESSE). Namely, in this study we compared two different types of intervention, which would allow a shorter time for the acquisition of the social tasks proposed. In particular, the hypothesis verified in the work continues to be that the intervention based on the use of VR can allow a faster acquisition, but the sample taken into consideration is more representative than the previous study [38]. We believe that this intervention may be useful for the support of social skills of individuals on the autism spectrum, with a possible impact on daily life, and is listed among the research priority areas [41] established both by researchers and autism communities (practitioners, individuals on the autism spectrum and their family members).

2. Materials and Methods

2.1. Participants

The study comprised 60 individuals who had received a diagnosis of ASD level 1, as reported by the diagnostic criteria of DSM 5 [3]. All the individuals share the same socio-cultural background of the parents and are originally from the city of Caserta. The family context and the and environmental context was not considered to impact the level of education in either group. All individuals were administered the Wechsler Intelligence Scale for Children (WISC IV) [42] in order exclude any individuals with impaired intellectual abilities, hence a comorbidity with intellectual disability. For this reason, the inclusion criteria were the following: (a) aged between 9 and 10 years, (b) diagnosis of level 1 ASD (emerged from administration of ADOS2/Module 3 [43] and confirmed by administration of K-SADS-PL DSM 5 [44], (c) absence of other nosographically defined psychiatric pathologies and (d) IQ ≥ 97.

After the subsequent confirmation of the diagnosis and the prospect of inclusion in the sample, we randomly divided the individuals into two experimental groups comprising 30 individuals each. The individuals of the two groups had the same inclusion criteria and did not show a difference in socio-cultural factors. The first experimental group (Gr1) was composed of 30 individuals with a mean age of 9.3 (SD 0.63) and a mean IQ of 103.00 (SD 1.70), of which 25 were males and 5 were females. The Gr1 group performed a VR intervention (VRI). The second experimental group (Gr2) was composed of 30 individuals with a mean age of 9.4 (SD 0.49) and mean IQ of 103.13 (SD 2.04), of which 26 were males and 4 were females, and mean SES value of 7.43 (SD 0.62). The Gr2 group underwent an individual intervention with the therapist (IIT). No significant differences in age or intelligence quotient total (QIT) in the two groups were observed. We established that the socio-cultural class differences between the groups were negligible by administering the assessment to the parents of the children in order to determine their socio-economic status (SES). The assessment was carried out by administering the Socio-Economic Level Assessment to the parents. The Gr1 group had a score of 7.3 (SD = 0.6), and the Gr2 group had a score of 7.5 (SD = 0.3). To calculate the significance of the data of the inclusion criteria we used the independent sample t test. The data are shown in Table 1.

Data were collected in the laboratory of modern technologies of the University of International Studies of Rome (UNINT) by psychologists authorized in collaboration with the University of Naples Federico II, the University of Salerno and the University of Campania “Luigi Vanvitelli”.

All procedures performed in this study were in agreement with the ethical standards of the UNINT Ethics Committee and the 1964 Declaration of Helsinki and its subsequent amendments and equivalent ethical standards. Furthermore, informed agreement was obtained from all caregivers of the participants that took part in the study.

2.2. Instruments

The protocol followed for sample recruitment consists of different tests, namely the Wechsler Intelligence Scale for Children (WISC-IV) [42], Autism Diagnostic Observation Schedule 2 (ADOS 2-Module 3) [43], the diagnostic interview for the evaluation of psychopathological disorders in children and adolescents (K-SADS-PL DSM-5) [44] and the scale for the evaluation of socio-economic status (SES) [45].

WISC-IV is a clinical tool [42], administered individually, to appraise the cognitive skills of children aged between 6 and 16 years of age. It allows for the calculation of the intellectual quotient (IQ) which represents the overall cognitive capacity of the child. The IQ is obtained from 4 scores: the verbal comprehension index (VCI), visual perceptual reasoning index (PRI), working memory index (WMI) and processing speed index (PSI).

ADOS 2-Module 3 is a structured observation [43] constituting 14 activities with 28 correlated scores. Activities involve important social, communicative and linguistic behaviors with fluent children and adolescents. The module has three specific objectives. The first is to observe the spontaneous social communication behavior of the subject for a given situation that provides a stimulus to communicate or interact. The second is to evaluate the child ability to act properly for a given situation (e.g., a story or teaching a task). Thirdly, it allows the examiner to observe the individual’s sense of humor and creativity.

K-SADS-PL DSM-5 is a diagnostic interview [44] based on the DSM-5 criteria for the assessment of psychopathological disorders (both past and present) within infancy and adolescence. The main purpose is to identify psychotic disorders, attention deficit disorders and upsetting behavior, mood disorders, and anxiety disorders including abuse of substances.

SES is a questionnaire, in the form of a self-report [45], which collects data about the socio-cultural level of the parents.

2.3. Procedures

All individuals were administered WISC-IV for the assessment of intellectual functioning (IQ inclusion criterion ≥ 97). For the diagnostic evaluation of HFA, we used ADOS 2 Module 3 and K-SADS-PL (DSM-5) both for diagnostic classification and exclusion of further psychiatric pathologies. The 60 selected participants were randomly split into two groups. The two groups received two different interventions.

Intervention 1: VR Intervention (VRI). VR emotional literacy intervention involved the 3D projection of two sequences of scenes recorded with the same actors of the photos used for the Gr1 intervention. The first sequence included 38 scenes of which 14 referred to the 7 primary emotions and 24 referred to the 12 secondary emotions. The second sequence involved the projection of 38 scenes of which 14 referred to primary situations and emotions and 24 referred to secondary situations and emotions. The scenes projected as outlined are the same from which the photos for the IIT intervention were taken, so there was always alternation between the adult protagonist and the child protagonist (Figure 1).

Intervention 2: Individual Intervention with the Therapist (IIT). This is an emotional literacy intervention carried out using 76 photos in sequence shown to the children and adults. The first 38 sequences were created through the use of specially recruited actors. Specifically, the subject with HFA was presented with 14 photographs relating to the recognition of the 7 primary emotions (2 for each primary emotion, one on children and the other on adults) and 24 photographs relating to the recognition of the 12 secondary emotions (2 for each emotion, one on children and the other on adults). For both sequences of primary emotions and secondary emotions, the presentation of the photos was randomized; during the presentation of the images, the child was asked to recognize the emotion depicted in each single photo. A further sequence of 38 photos was then administered to the individuals with HFA. The situational scenario preceding the photo was described, and then the image depicting the emotion corresponding to the situation was presented. The situations were correlated for 14 photos to primary emotions and for another 24 photos to secondary emotions: For these cases there was always a photo relating to an adult and one relating to a child.

In both groups the same emotional literacy training was carried out in different ways. In intervention 1 (Gr1), videos were projected through a 3D viewer in VR. In intervention 2 (Gr2) the training involved exposure to cardboard images used by a therapist individually. The VR videos and cardboard images depicted the same scenes. The training was entirely provided three times per week on three different days. To evaluate the acquisition of the skills foreseen by the 4 sequences (recognition of primary or basic emotions (PE), recognition of secondary emotions (SE), emotions and situations for primary emotions (ESPE), emotions and situations for secondary emotions (ESSE)), a weekly test was planned with 38 items (7 for primary emotion recognition, 12 for secondary emotions, 7 for primary emotions and situations, 12 for secondary emotions and situations), through images that varied from week to week. Answers that were 100% correct were used as the acquisition criterion. The image scenes used were different during the training and during the learning procedure (different images were used for the test).

The duration of the training was 3 months, 3 times a week. Participants included in the sample had attended all meetings, while participants who were inconsistent were excluded from the sample.

At T0 pre-training no subject had already reached the acquisition criterion for the 4 trials. The initial condition for individuals in the two groups was set in order to have a score equal to zero on all four tasks.

3. Results

We performed statistical analysis on the data with the SPSS 26.0 [46] software. Significance was accepted at the 5% threshold (α < 0.05). ANOVA methods were used to compare the scores that were derived from the measurement of acquisition times to the four proposed tasks: recognition of primary or basic emotions (PE), recognition of secondary emotions (SE), emotions and situations for primary emotions (ESPE) and emotions and situations for secondary emotions (ESSE). At T0 pre-training no subject had already reached the acquisition criterion for the four trials.

Following the literacy intervention (T1), significant differences emerged with respect to the acquisition times for the four tasks proposed between Gr1 and Gr2. More specifically, individual tasks of both groups were compared at T0 and T1, to establish which of the two interventions methods were more effective.

Next, both groups were compared at T1 (between-group). A 2 × 2 mixed two-way univariate ANOVA was used, with factor within groups = time (T0 and T1) and factor across the two groups = group (Gr1 and Gr2) for a single task.

Regarding task 1 (PE), it was highlighted that:

• -. The factor within-time was significant (F (1,58) = 2267.395; p < 0.05), indicating the presence of a change over time; hence, it shows that the two interventions were successful (Table 2).

• -. The factor across the groups was non-significant (F (1,58) = 1.349, p = 0.25) showing no differences between group 1 and group 2, so it is evident that both treatments are effective for the recognition tasks of PE (Table 3).

• -. A non-significant time * group interaction was obtained (F (1,58) = 1.349, p = 0.25), indicating the absence of an interaction between the type of treatment and the time. Both treatments showed efficacy for the PE recognition task in both groups (Table 4).

Regarding task 2 (SE), it was highlighted that:

• -. The within-time factor was significant (F (1,58) = 89.136; p < 0.05) indicating the presence of a change over time; hence, both interventions were effective (Table 5).

• -. The factor between the group was significant with F (1,58) = 28.94, p < 0.05, showing the occurrence of a variance over the two groups (1 and 2); thus, outcomes reveal a significant difference between the two interventions, showing greater effectiveness in favor of the VR intervention when compared to the other treatment (Gr1) (Table 6).

• -. Time * group interaction was significant resulting in F (1,58) = 17.31, p < 0.05, and revealing the presence of a significant interaction across the time and the type of intervention. Although both treatments showed efficacy, the VR intervention appeared as more effective (Table 7 and Figure 2).

Regarding task 3 (ESPE) it was highlighted that:

• -. The within-time factor was significant (F (1,58) = 1331.692; p < 0.05) revealing the occurrence of a change over time; thus, it is evident that the two compared treatments were adequate (Table 8).

• -. The factor between the group was significant demonstrating F (1,58) = 23.339, p < 0.05, thus revealing the presence of a difference between the two groups; hence, a significant difference exists between the two treatments, in which the VR intervention revealed a greater effectiveness (Gr1) (Table 9).

• -. Time * group interaction was significant (F (1,58) = 21.745, p < 0.05), indicating that a significant interaction can be observed between the type of treatment and the time. Although both treatments showed efficacy, the VR intervention revealed greater effectiveness (Table 10 and Figure 3).

Regarding task 4 (ESSE) it was highlighted that:

• -. The factor within-time was significant (F (1,58) = 3016.147; p < 0.05), showing that a change over time occurred, so both interventions were effective (Table 11).

• -. The between-group factor was significant (F (1,58) = 125.117, p < 0.05). This outcome reveals the presence of a difference between groups (1 and 2); hence, a significant variance exists across the two treatments, but the VR intervention was more effective (Gr1) (Table 12).

• -. Time * group interaction was significant (F (1,58) = 115.835, p < 0.05). This outcome reveals that a significant interaction between the type of intervention and time exists. Both treatments showed efficacy, but more so for the VRI (Table 13 and Figure 4).

4. Discussion

The support of development skills is listed among the research priorities established both by autism researchers and autism communities (practitioners, individuals on the autism spectrum and family members) since it may have a positive influence on daily lives [41]. Emerging technologies such as VR help us to study ASD and offer promising techniques to support social skills. The development of VR environments has allowed for the creation of new training and intervention tools which may be more effective than traditional methods as demonstrated by preliminary studies [35,47,48]. VR can simulate real-life situations for children to explore safely, and it can also be possible to create environments that are difficult to experience in everyday life [25]. VR environments (VREs) provide a three-dimensional perspective that mimics reality. In games such as World of Warcraft or Fortnite, users can navigate their digital world in a three-dimensional environment comparable to the real world. Furthermore, all of VR has multiple interactive properties [49,50]. Sometimes, these interactive properties are basic, such as having the ability to change the user’s digital point of view (looking around). At other times the interactive properties are more advanced, such as moving in the digital environment, interacting with objects and communicating with other people. This technology is very encouraging and gratifying, especially for individuals with ASD [30], offering an interactive, engaging and personalized platform for the training and the support of social cognition within these individuals.

Previous studies have highlighted how VR interventions may support people on the autism spectrum with the ability to recognize the emotions of others by their faces [51] and through their tone of voice [52]. Our idea is precisely that interventions in VR can lead to a better and more stable acquisition of social skills over time, as described in a previous study [38]. In that previous study the sample size was small; therefore, in this study we increased the sample size and compared two types of intervention for the enhancement of social skills. Our analysis has shown that the acquisition times for the recognition of primary emotions is the same for both intervention methods (VR and traditional). However, regarding the tasks that involved exposure to situations for the use of primary and secondary emotions, the acquisition times were shorter with the use of VR. This intervention highlighted significant differences in group 1 as the representation of the situations together with the 3D experience of the scene helps the subject to develop the competence first and a better implementation of such competences in virtual everyday life also follows. Instead, the simple comment of a photograph through individual intervention with the therapist could not speed up the acquisition of competence. We hope that this powerful practice carried out in diverse VR scenarios can aid the generalization of learned social abilities to real routine life contexts [21,53,54]. These studies used different everyday life scenarios (having coffee in a bar, walking with a friend, etc.) and highlighted rapid gain of social qualities and the recognition of emotions. With this study, we verified our hypothesis that the intervention in VR could allow faster acquisition.

Therefore, virtual reality interventions can support individuals on the autism spectrum in their capabilities to recognize the emotions of others from their faces and also in social situations. However, we did not specify whether such acquisition could be faster for primary or secondary emotions. Our analyses instead highlighted a specific difference, namely that the acquisition of social skills is faster with social situations. We therefore contributed to adding further evidence to the studies on social skills interventions in VR, even if some limitations emerged, as described below.

5. Limits and Conclusions

VR is an interactive and perceivably challenging approach for individuals with HFA, especially as a treatment for enhancing social skills. These data, together with previous preliminary data [38], suggest that VR can be a dynamic and effective practice for supporting basic and complex social skills. Our study was particularly focused on children with HFA; therefore, more research is needed to investigate whether the findings of our studies are also present in individuals with different levels of autism.

Furthermore, it could be interesting and useful to investigate the differences in the acquisition of recognition skills (both for facial expressions and for matching to social situations) of primary and secondary emotions in order to plan more specific and targeted interventions for these individuals.

Another limitation of our study is that our sample mainly included male participants, consistent with a higher male prevalence of the condition. Further studies are required to establish if females exhibit similar characteristics or if they react differently to social stimulation. Moreover, future studies may evaluate whether the social skills learnt through the VR may not only be implemented in virtual everyday life situations but also in real everyday life situations by comparing different groups of individuals. It is necessary, in subsequent works, to use larger samples to further examine the replicability of these results and to evaluate the maintenance of the skills developed in the medium and long term.

Author Contributions

Conceptualization, A.F. and M.C.R.; methodology, M.C.R.; software, M.C.R.; validation, A.B., E.S. and F.D.C.; formal analysis, M.C.R.; investigation, A.R.; resources, M.C.; data curation, E.S.; writing—original draft preparation, M.C.R. and F.D.C.; writing—review and editing, A.F. and G.S.; visualization, M.C.; supervision, A.R. and G.S.; project administration, A.F. and M.C.R. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Ethics Committee of UNINT.

Informed Consent Statement

Informed consent was obtained from all caregivers of the participants included in the study.

Data Availability Statement

The data is available from the corresponding author.

Conflicts of Interest

The authors declare no conflict of interest.

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Figures and Tables

Figure 1. Description of procedures.

Figure 2. Observation between the two groups at T0 and T1 on task 2 (ES). Groups 1 and 2 comparison at T0 and T1 on task 2 (ES).

Figure 3. Comparison of the two groups between T0 and T1 at task 3 (ESPE). Comparison of the group 1 and 2 between T0 and T1 on task 3 (ESPE).

Figure 4. Comparison of the groups at T0 together with T1 on task 4 (ESSE). Comparison of the two groups between T0 and T1 at task 4 (ESSE).

Table 1

Statistical data of the inclusion criteria.

	Group 1		Group 2
	Mean	S	Mean	S	T	p
VCI	100.40	1.32	100.40	1.42	0.00	1.000
PRI	116.96	3.98	117.13	4.28	−0.156	0.877
WMI	94.50	2.73	94.50	2.50	0.00	1.000
PSI	92.40	1.88	92.40	1.88	0.00	1.000
QI	103.00	1.70	103.13	2.04	−0.274	0.785
ADOS	7.50	0.50	7.53	0.50	−0.254	0.800
SES	7.30	0.60	7.50	0.30	−0.266	0.675

Table 2

Effect of within factor on task 1 (PE).

T0		T1		F	p
Mean	SD	Mean	SD
4.26	0.44	7.00	0	2267.395	<0.05 *

* the accepted significance is p < 0.05.

Table 3

Impact of between factor (group) on task 1 (PE). Effect of between factor (group) on task 1 (PE).

Group 1		Group 2		F	p
Mean	SD	Mean	SD
5.66	1.38	5.60	1.44	1.349	0.250

Table 4

Effect of time * group interaction on task 1 (PE).

Time	Gr1		Gr2		F	p
	Mean	SD	Mean	SD
T0	4.33	0.47	4.20	0.40
T1	7.00	0	7.00	0	1.349	0.250

Table 5

Effect within factor on task 2 (SE).

T0		T1		F	p
Mean	SD	Mean	SD
6.26	0.75	10.50	3.53	89.136	<0.05 *

* the accepted significance is p < 0.05.

Table 6

Impact of between factor (group) on task 2 (SE). Effect of between factor (group) on task 2 (SE).

Gr1		Gr2		F	p
Mean	SD	Mean	SD
9.31	3.76	7.45	2.49	28.894	<0.05 *

* the accepted significance is p < 0.05

Table 7

Effect of time * group interaction on task 2 (SE).

Time	Gr1		Gr2		F	p
	Mean	SD	Mean	SD
T0	6.26	0.69	6.26	0.82
T1	12.36	3.01	8.63	3.01	17.331	<0.05 *

* the accepted significance is p < 0.05

Table 8

Impact of within-factor on task 3 (ESPE). Effect of within factor on task 3 (ESPE).

T0		T1		F	p
Mean	SD	Mean	SD
3.28	0.45	17.50	3.53	1331.692	<0.05 *

* the accepted significance is p < 0.05.

Table 9

Effect of between factor (group) on task 3 (ESPE).

Gr1		Gr2		F	p
Mean	SD	Mean	SD
11.35	8.36	9.43	6.06	23.339	<0.05 *

* the accepted significance is p < 0.05.

Table 10

Effect of time * group interaction on task 3 (ESPE).

Time	Gr1		Gr2		F	p
	Mean	SD	Mean	SD
T0	3.33	0.47	3.23	0.43
T1	19.367	3.01	15.63	3.01	21.745	<0.05 *

* the accepted significance is p < 0.05.

Table 11

Effect of within factor on task 4 (ESSE).

T0		T1		F	p
Mean	SD	Mean	SD
4.73	0.68	26.25	5.25	3016.147	<0.05 *

* the accepted significance is p < 0.05.

Table 12

Effect of between factor (group) on task 4 (ESSE).

Gr1		Gr2		F	p
Mean	SD	Mean	SD
17.70	13.20	13.28	8.90	125.117	<0.05 *

* the accepted significance is p < 0.05.

Table 13

Effect of time * group interaction on task 4 (ESSE).

Time	Gr1		Gr2		F	p
	Mean	SD	Mean	SD
T0	4.83	0.64	30.56	3.43
T1	4.63	0.71	21.93	2.42	115.835	<0.05 *

* the accepted significance is p < 0.05.

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