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Review

Documentary Analysis of the Scientific Literature on Autism and Technology in Web of Science

by
Noemí Carmona-Serrano
1,
Jesús López-Belmonte
2,*,
José-Luis Cuesta-Gómez
3 and
Antonio-José Moreno-Guerrero
2
1
Ceuta Autism Association, University of Granada, 51001 Ceuta, Spain
2
Department of Didactics and School Organization, University of Granada, 51001 Ceuta, Spain
3
Department of Education Sciences, University of Burgos, 09001 Burgos, Spain
*
Author to whom correspondence should be addressed.
Brain Sci. 2020, 10(12), 985; https://doi.org/10.3390/brainsci10120985
Submission received: 3 November 2020 / Revised: 29 November 2020 / Accepted: 11 December 2020 / Published: 14 December 2020
(This article belongs to the Special Issue Advances in Autism Research: Series II)
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Abstract

:
The objective of the study is to track the progression of the scientific literature on autism and the technology applied to this disorder. A bibliometric methodology has been used, based on a co-word analysis. The Web of Science database was chosen to perform the analysis of the literature. A unit of analysis of 1048 publications was configured. SciMAT software was used mainly for document analysis. The results indicate that the first studies appeared in 1992, but it was not until 2009 that the research volume increased considerably. The area of knowledge where these studies were compiled was rehabilitation, which marks the truly therapeutic nature of this type of study. One of the authors with the most studies, as well as the most relevant research, was Sarkar, N. Manuscripts were usually research articles written in English. It could be concluded that research in this field of study focused mainly on interventions carried out through the use of technological resources, with students or young people who present with ASD. This line of research, although not the only one, was the most relevant and the one that had aroused the most interest among the scientific community.

1. Introduction

Autism spectrum disorder (ASD) is defined as a set of neurodevelopmental disorders that encompasses a multifactorial perspective. Science reveals that almost 1.5% of the world’s population suffers from this disorder [1]. ASD mainly reflects alterations in the field of socialization of people [2]. In addition, people with ASD can have communication disorders, as well as repetitive and stereotyped behaviors [3]. Likewise, people with ASD can present deficits in different aspects such as executive functioning, sensory perception, and attention, and can even develop depression [4].
Along these lines, people with this disorder may present signs of aggressiveness, challenging behaviors, and restricted interests [5]. In addition, people with ASD can suffer from anxiety disorders [6]. This can lead to emotional problems [7] at a higher level than seen in people considered to have typical development [8]. All of the above can be increased exponentially if the person with ASD has a low cognitive level [9].
In addition, people with ASD may have difficulties planning daily tasks or actions [10]. They may also exhibit alterations in the structure and use of language [11]. People with ASD may also have writing skills at a lower level than other people [12]. All these singularities that make up ASDs can coexist with other types of pathologies, such as intellectual disability and altered sensory processing [13]. However, people with ASD can process colors with a high level of precision [14]. In this sense, they can also show great musical abilities [15].
Despite the wide range of symptoms, the alteration of the sensory plane is postulated as the main change in people with ASD [16]. At a sensory level, people with ASD can have an altered sense of touch, which is a relevant sense for contact between people [17]. Similarly, people with ASD may have unusual responses to the sounds they perceive around them because they do not process external stimuli in the same way as other people [18]. Another limitation can be seen in motor development. People with ASD can have serious difficulties performing certain tasks of daily life. This can affect both their quality of life and autonomy [19]. Continuing on the sensory plane, the sense of sight can also involve different processing, especially with regard to focusing the gaze on human faces. The reason for this is the hypoactivation of the fusiform area of the face [20]. Therefore, people with ASD may present a set of needs that must be attended to by specialists [21,22,23].
Regarding gender, the scientific literature indicates that women show behaviors and attitudes that are not as restricted and repetitive as men. This is due to sex-linked differences in brain networks. In particular, the difference is seen in networks linked to social and corticosteroid integration [24]. Clinically, the diagnosis of ASD is based on phenotype. Despite this, there are no drugs for its treatment. This leads to therapeutic intervention as the most productive measure for the treatment of previously diagnosed disorders [25].
Early treatment through interventions can lead to substantial improvements in the capacities of people with ASD [26,27]. The practices carried out should be based on observation so that people with ASD can imitate the appropriate behaviors modeled by therapists [28]. All of this will allow for the acquisition of new skills that will have a positive impact on their daily life [29].
Research reveals relevant results from those interventions carried out with technological resources. In this sense, technology-mediated interventions provide people with ASD with a number of benefits [30]. Among them, the improvement of responsibility stands out [31]. Likewise, technology in its different formats (electronic resources, mobile applications, and immersive environments) favors the autonomy of people with ASD. Despite the potential for its use in this population, the design and interface of the technology are currently being analyzed. All this is meant to achieve better adaptation to the needs of people suffering from this disorder [32].
Technological interventions through augmented reality, virtual reality, robotic devices, and mobile applications have shown great advantages. These technologies have obtained improvements in social skills, participation with their immediate environment, communication with other people, and the processes of assimilation and retention of information [33,34,35,36]. However, there are still issues that technology has not been able to address, such as the regulation of emotions [37].
Therefore, technology is positioned as a relevant resource to achieve effective interventions in people with ASD. This will bring about various benefits that will result in a positive integration into society [38,39]. In summary, the use of technology in people with ASD has great potential [40].

Justification and Objectives

In this work, the relationship between the terms “autism” and “technology” (ASD-TECH) is analyzed through a bibliometric perspective of the literature [41,42]. For this, the Web of Science (WoS) database was chosen as the object of study. This choice is due to it being one of the largest databases in the world.
The novelty of this study lies in its innovative analysis technique. Specifically, a performance analysis and scientific mapping of the documents reported on these constructs were carried out. For a correct and adequate analytical procedure, the protocols established in previous impact studies were followed. This will allow for the reduction of bias in the research [43,44].
Therefore, this work focuses on analyzing the significance and evolution of ASD-TECH in the scientific documents collected from WoS. An initial search was carried out in this database, and no work similar to this one was found. The purpose of this study is to reveal to the scientific community the progress, and upcoming trends [45] on ASD-TECH collected in the WoS literature. This will contribute to the establishment of knowledge about the literature concerning ASD and the technology applied to the treatment of this disorder.
The objectives of this study are to (a) trace the research on ASD-TECH in WoS; (b) determine the scientific evolution on ASD-TECH in WoS; (c) Discover the most relevant topics about ASD-TECH in WoS and (d) locate the most representative authors on ASD-TECH in WoS.

2. Materials and Methods

2.1. Research Design

The research was based on a bibliometric methodology to achieve the objectives. The potential of this methodology is focused on the quantification and comprehensive evaluation of scientific publications [46,47]. The design of this study will allow for a pertinent survey of the existing literature on bounded contexts [48].
Specifically, the research design focuses on an analysis of co-words [49] and on the study of various indicators related to documentary impact (index h, g, hg, and q2) [50]. The different actions carried out during the research development will allow for the generation of maps with nodes to reveal the performance, the location of the conceptual subdomains, and the thematic development [51] linked to ASD-TECH in the WoS database.

2.2. Procedure

Following the procedural guidelines for previous research on this type of study, this work has had various phases [52,53]. The first phase focused on selecting the database (WoS). The second phase focused on the concretion of the concepts to carry out the search (autism, ASD, ICT, and technology). The third phase brought together the preparation of the search equation: (“autism” OR “ASD”) (TITLE) AND (“ICT” OR “technolog*”) (TOPIC). The fourth phase consisted of applying the equation in the main WoS collection (SCI-EXPANDED, SSCI, A and HCI, CPCI-S, CPCI-SSH, BKCI-S, BKCI-SSH, ESCI, CCR-EXPANDED, and IC indices).
The completion of these phases gave rise to a total of 1192 publications. This documentary volume was then refined using different criteria [54]. The exclusion criteria were: documents published in 2020 (n = 120); repeated or poorly indexed documents in WoS (n = 24). The application of these criteria produced a final unit of analysis of 1048 publications. Figure 1 contains a flowchart based on the PRISMA protocol that synthesizes the actions carried out.
For the presentation of the results on the performance and scientific production, various inclusion criteria were established [55,56]: Year of publication (all except 2020); Language (x ≥ 10); Publication area (x ≥ 100); Type of documents (x ≥ 100); Organizations (x ≥ 30); Authors (x ≥ 15); Sources of origin (x ≥ 20); Countries (x ≥ 40); the four most cited documents (x ≥ 245).

2.3. Data Analysis

Various analytical tools such as Analyze Results, Creation Citation Report, and SciMAT were used. The Analyze Results and Creation Citation Report applications were used to report the year, authorship, country, type of document, institution, language, medium, and most cited documents. SciMAT software was used to carry out the structural and dynamic development of the publications from a longitudinal perspective. The guidelines of previous studies that have used these tools for the correct development of the analysis were followed [57,58].
In addition, SciMAT was used to perform a co-word analysis. This specific analysis is produced in various actions [59]:
  • Recognition: It consisted of the analysis of the keywords (n = 3829) reported from the extracted publications. In addition, maps of co-occurrence nodes were generated. A normalized network of co-words was made. The keywords with the highest significance were selected (n = 3543). Outstanding themes and concepts were delimited through a clustering algorithm.
  • Reproduction: Various thematic networks were designed, as well as strategic diagrams. These diagrams are made up of four quadrants. The upper right quadrant contains the relevant and motor topics. The upper left quadrant brings together entrenched and isolated issues. The lower left quadrant welcomes the issues in disappearance or projection. The lower right quadrant reveals the underdeveloped and cross-cutting themes. In the performance of reproduction, the principles of density and centrality intervene. Density establishes the internal strength of the network. Centrality determines the level of connection of a network with others [60].
  • Determination: The documentary package was articulated in different time periods, with the purpose of analyzing the evolution of the nodes in time. In this study, three periods were configured (P1 = 1992–2012; P2 = 2013–2016; P3 = 2017–2019). The configuration of these periods started from the criterion of similarity of the documentary volume between each of them. To establish the strength of association between the periods, we started from the number of common keywords. However, for the analysis, a single period was used (PX = 1971–2019).
  • Performance: Various production indicators linked to inclusion criteria were established [61] (Table 1).

3. Results

3.1. Scientific Performance and Production

The first mention of ASD-TECH in WoS dates back to 1992. Since then, studies on this topic have proliferated. This evolution has two clearly differentiated periods. In the first—1992 to 2009—the research volume was relatively low. The second period, 2010 to 2019, was when the research volume grew exponentially year by year. The production peak occurred in 2019 (Figure 2).
Manuscripts dealing with ASD-TECH are mainly written in English. Other languages are used, but these show minimal production with respect to English (Table 2).
Research on ASD-TECH is mostly collected in the area of rehabilitation knowledge, although it is closely followed by the areas of developmental psychology and special education (Table 3).
ASD-TECH studies mostly use research articles to disseminate results. These are followed by conference papers and systematic reviews (Table 4).
There are three institutions that are currently pioneering ASD-TECH research. These are the University of California, Vanderbilt University, and the University of North Carolina (Table 5).
In the study of ASD-TECH, there is one author who has produced, to date, the largest volume of research on the subject. This is Sarkar, N. Two other authors are close behind (Table 6).
The main source of studies on ASD-TECH is the Journal of Autism and Developmental Disorders. The research volume is almost double that of Lecture Notes in Computers Science, which is the second-largest source (Table 7).
The country with the highest volume of research on ASD-TECH is the United States. Other countries are far behind (Table 8).
Of the four most-cited manuscripts on ASD-TECH (Table 9), the study by Klin et al. (2001) stands out from the rest of the manuscripts with a total of 1137 citations. This research concluded that individuals with autism present abnormal patterns of the visual location at the social level, with less attention to the eyes and more focus on the mouth, bodies, and objects (Table 9).

3.2. Structural and Thematic Development

The keywords in each of the collected WoS manuscripts show a disparate trend, over the established periods, in terms of the number of words. In this case, the first period has a much lower volume than the second and third periods. The latter has an even volume of production. Where there is coincidence is in the percentage of coincidence between periods. The percentage is between 35% and 36% (Figure 3). These figures indicate that there is a medium-high volume of coincidence in scientific production. In other words, there are overlapping lines of research in the field of ASD-TECH in the three established time periods.
The analysis of thematic performance, based on various bibliometric indicators, as shown in Table 10, provides information on the topics most researched by the scientific community. In this case, in the first period (1992–2012), the subject matter with the greatest bibliometric value is “children.” In the second period (2013–2016), the topic with the highest bibliometric value is “intervention.” In the last period (2017–2019), the subject with the highest bibliometric value is again “children.” In all these cases, the values of these themes were much higher than the rest.
The strategic diagram, taking into account in this case index h as the main reference, shows the information on the relevance of the different themes in each of the established time periods (Figure 4). Depending on the location of the themes in the diagram, their relevance will be greater or lesser. In this case, the position of the subject is produced, taking into account its external connection (centrality) and its internal connection (density). In addition, the keywords that relate to the driving issues are listed in Appendix A.
In the first period (1992–2012), the themes considered as driving forces were “communication,” “intervention,” “prevalence,” “assisted reproductive technology,” and “copy number variation.” During this period, it can be seen that the main themes were communication with people with ASD, intervention for the improvement of those affected, and the prevalence of representations of ASD in society. It can also be seen that studies focused on assistive technology and chromosome analysis.
In the second period (2013–2016), the driving themes were “daily living skills,” “intervention,” “animated tutor,” “iPad,” “adults,” and “developmental disabilities.” In this period, the relevance of the studies varied slightly with respect to the previous period. In this case, we analyzed the skills needed to be able to function in daily life, interventions to minimize the difficulties caused by ASD, tutors who look after people with ASD, new technological resources such as iPads, adults with ASD, and possible developmental disabilities that can lead to a growth in the number of people with ASD.
In the last period (2017–2019), the motor themes “children,” “applied behavioral analysis,” “acquisition,” “daily living skills,” “Asperger’s syndrome,” and “skills.” In this period, the trends were slightly different again from previous periods. In this case, the most relevant studies focused on children, on the analysis of the behavior of subjects with ASD, on the skills of people with ASD, on the acquisition of competencies for social life, and on Asperger’s syndrome. In addition, since this was the final period, the topics “needs,” “Rett syndrome,” “vocabulary,” “anxiety,” and “prevalence” must also be considered. These themes, due to their position in the diagram, are considered to be unknowns. This is because they may be the future driving force or may be themes that have disappeared from the lines of research established by the scientific community.

3.3. Thematic Evolution of Terms

In the evolution of research on ASD-TECH, two aspects can be observed: the main research lines and the connections established between the different topics. The continuous lines show conceptual connections. In other words, these are connections in which the themes themselves contain other themes seen previously. The discontinuous lines show connections by means of keywords. When the width of the line, both continuous and discontinuous lines, is greater, it means there is a greater number of coinciding themes or keywords between themes. Therefore, the wider the line, the closer the relationship.
Analyzing Figure 5, it can be seen that there is a theme that is repeated in all three periods, such as “assistive reproductive technology,” which can be considered a line of research in this field of study. This does not mean that it is the most relevant or the only one. In this case, it can be seen that the mainline of research is “intervention—children.” That is, ASD-TECH research is mainly focused on therapeutic interventions in minors. In this field of study, other lines of research are observed, in addition to those previously established, such as “people–virtual_reality” and “communication—iPad skills,” although they are not as relevant as the one indicated above. One aspect to highlight in the analysis of the figure is that more nonconceptual connections are observed than conceptual ones. This means that the lines of research are differentiated from each other, and so far, there are no implications of the main lines of research for each other.

3.4. Authors with the Highest Relevance Index

The strategic diagram of scientists in the ASD-TECH branch of the study shows that Porayska-Pomsta, K., Stasolla, F., and Sarkar, N., are the most relevant authors in this line of research. Furthermore, the authors Marschik, P. B., Chetouani, M., and Anderson, A., should be taken into account since their position in the diagram places them as possible relevant authors of ASD-TECH studies in the future (Figure 6).

4. Discussion

The purpose of the study was to assess the importance of scientific publications on autism linked to the technological field. We live in a society marked by continuous advances in technology [52]. Innovative and electronic resources are increasingly widespread in all areas of life [44]. For this reason, the need arises to check the state of the links between ASD and technology. This is reflected in the literature, which shows the role of technology in the field of ASD [30,31,32,33,34,35,36,37,38,39,40]. Therefore, given the peculiarities of an increasingly innovative and technological society, it is pertinent to focus on how this disorder is treated from a technological point of view. For this, an analysis was carried out of everything collected in the scientific literature so far.
First, the performance analysis allows for a general evaluation of the studies carried out on the ASD-TECH topic. The first scientific research on ASD-TECH was in 1992. From then until 2019, a differentiated evolution can be observed in two periods: a first period, between 1992 and 2009, when the research was scarce and linear in time. In the second period, from 2010 to 2019, there was a considerable increase in research, with growth year by year. The differentiation of the two periods may be linked to the increase and improvement in technological resources in the social sphere, which was then transferred to other fields, such as the treatment and care of ASD. It should also be noted that the peak of research production was in 2019.
The main type of manuscript used to present scientific results is research articles, which are usually written in English. This shows that the research is grounded in time and that trends in this type of study are related to field studies. In addition, the main area of knowledge, where these studies are collected is rehabilitation. This shows that technological resources are used for the rehabilitation of people with ASD.
There is no single relevant institution that dominates this field of study; the three main centers of research are the University of California, Vanderbilt University, and the University of North Carolina. Among the most noteworthy authors is Sarkar, who, as well as having the greatest volume of research, is one of the most relevant researchers, according to the analyses carried out. In this case, he can be considered a key reference in studies on ASD-TECH. This does not mean he is the only author to be considered; attention should also be paid to Marschik, Chetouani, and Anderson, since they may be among the main researchers in this field of study.
Among the different sources that disseminate to the scientific community the findings on this subject, there is the Journal of Autism and Developmental Disorders. Its volume of production is quite high. In addition, the country with the highest volume of production is the United States. Among the most frequently cited articles is that of Klin et al. (2001), which focuses on the attention that people with ASD pay to their social interactions. His citation volume is very high compared to other manuscripts dealing with this line of research.
In terms of the structural and thematic development, it can be seen that the level of coincidence between periods is over 35%. This shows that the scientific community, although it can establish new lines of research, maintains lines of study that are the basis for this type of research.
The thematic performance shows two themes with the highest bibliometric values in this field of study. One is “children,” which is repeated in the first and last periods; the other is “intervention,” which dominated the second period. This indicates how the direction of research on ASD-TECH is focused by the scientific community on children and intervention.
The strategic diagram indicates that there are changes in the driving themes of the three periods analyzed. In the first period, the most relevant studies focus on the communication of subjects presenting with ASD, on the various intervention techniques used with people with ASD, on the prevalence of the population presenting ASD, on assistive technology, and on chromosome studies of people with ASD. In the second period, the most relevant studies focus on the analysis of the skills needed to be able to function in daily life, interventions to minimize the difficulties arising from ASD, the tutors who attend to people with ASD, newly emerging technological resources such as iPads, adults with ASD, and the possible developmental disabilities that can result in a rise in the number of people with ASD. Finally, in the last period, studies focused on children, the analysis of the behavior of people with ASD, the skills of people with ASD, the acquisition of competencies for social life, and Asperger’s syndrome. This indicates that the focus of research has changed. Furthermore, we must take into account the themes of “needs,” “Rett syndrome,” “vocabulary,” “anxiety,” and “prevalence,” which may be the driving forces in this line of research.
Thematic developments have shown that there are more nonconceptual than conceptual connections. This indicates that there are independent lines of research in this field of study. Furthermore, a line of research is shown that remains, at a thematic level, constant over time, as is the case with “assistive reproductive technology,” given that it is the only theme that is repeated in all three periods. Furthermore, the connection established between them is conceptual. Thanks to this theme, this field of study does not present a conceptual gap. However, it turns out that this line of research is not the most relevant one over time. In this case, the main line of research is “intervention—children” because its connections are conceptual and thicker than the other established connections. For this reason, it can be said that research on ASD-TECH focuses mainly on therapeutic intervention in young people who have ASD.

5. Conclusions

The main conclusion that can be drawn from this investigation is that the ASD-TECH line of research has become relevant, in terms of production volume, over the last 10 years. Research in this field of study is mainly focused on interventions carried out, through the use of technological resources, with students or young people who present with ASD. This line of research, although not the only one, is the most relevant and the one that arouses the most interest among the scientific community.
This research focuses on offering both researchers and the different groups that attend to people with ASD information on the main trends in ASD-TECH studies.
The main limitations of the study are related to the purity of the database. This requires reading all of the manuscripts in order to know whether they meet the inclusion criteria established in this study. This represents an extra effort for researchers. Another limitation is the purification of the keywords. Many of them are poorly recorded or are presented differently, both by acronyms and by their full names. The authors have reviewed all the keywords, correcting and grouping them as necessary. Finally, another possible limitation of this study is the inclusion criteria, which, if modified, may lead to variations in the data presented. The criteria established in this study were based on the equity and volume of data. To this end, the authors have established various criteria, selecting the most appropriate ones. As a future line of research, field studies can be developed based on interventions through the use of technological resources, such as augmented reality.

6. Theoretical and Practical Implications

Both theoretical and practical implications can be drawn from this research. Among the theoretical implications, this study allows us to identify the most relevant and prolific institutions and authors on ASD-TECH, which provides researchers with relevant knowledge to assist with compiling adequate and interesting sources from this line of research. Furthermore, it facilitates the identification of the main scientific journals that publish the results obtained in the ASD-TECH line of research. It should also be noted that knowing the main lines of research generated in this field of study allows scientists themselves to guide the trends. In this case, they do not need to check what has been published previously; thanks to this research, they can know which lines of study they can establish. Finally, it can be said that this study makes it possible to provide more scientific literature on ASD-TECH. Among the practical implications is the fact that most research in this field of study is focused on minors and on interventions. This manuscript can be used by therapists themselves to discover new means of intervention, as well as to identify those interventions with the use of the most relevant technology and with the best results. Furthermore, this study provides families and therapists with the most relevant and significant journals in this field of study, speeding up the search for this type of scholarship.

Author Contributions

Conceptualization, N.C.-S. and J.-L.C.-G.; methodology, J.L.-B. and A.-J.M.-G.; software, A.-J.M.-G.; formal analysis, J.L.-B. and A.-J.M.-G.; investigation, N.C.-S., J.L.-B., A.-J.M.-G., and J.-L.C.-G.; data curation, A.-J.M.-G.; writing—original draft preparation, J.L.-B. and N.C.-S.; writing—review and editing, N.C.-S., J.L.-B., and A.-J.M.-G.; visualization, J.-L.C.-G.; supervision, J.L.-B. and N.C.-S. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Conflicts of Interest

The authors declare no conflict of interest.

Appendix A

Table
Table A1. Relationship between keywords and driving themes.
Table A1. Relationship between keywords and driving themes.
1992–2012
Driving ThemesKeywords
CommunicationAugmentative and alternative communication, feedback, spelling, speech-generating devices, behavioral analysis, language, learning and literacy
InterventionVocabulary, multimedia, recognize, adolescents, emotions, skills, Asperger’s syndrome and play
PrevalenceEpidemiology, birth, paternal age, cytokines, disorders, pregnancy, population, and autistic disorder
Assisted reproductive technologyChild and infantile autism
Copy number variationStructural variation and genetics
2013–2016
Driving ThemesKeywords
Daily living skillsVideo modeling, moderate, video prompting, computer-based intervention, intellectual disability, video, students, and self
InterventionAutism, young children, individual, adolescents, autism spectrum disorder, skills, technology, and Asperger’s syndrome
Animated tutorComputer-assisted instruction, emotion recognition, vocabulary, communication skills, computer, virtual environments, meta-analysis, and high-functioning autism
iPadPicture exchange, literacy, augmentative and alternative communicative, apps, behavioral intervention, parents, speech-generating devices, and communication
AdultsFunctioning autism, mind, usability, disorders, youth, attention, social media, and employment
Developmental disabilitiesLanguage, alternative communication, quality of life, assistive technology, mobile technology, social skills, transition, and young adults
2017–2019
Driving ThemesKeywords
ChildrenTechnology, autism, high-functioning autism, adolescents, adults, autism spectrum disorder, intervention, and spectrum disorders
Applied behavioral analysisSpecial education, technology perspectives, academic skills, exceptionality, methodology, outcomes, parents, and telehealth
AcquisitionAlternative communication, preschoolers, augmentative and alternative communication, communication skills, speech-generating devices, tablets, generalization, and language
Daily living skillsIndividuals, students, employment, activity schedules, intellectual disability, mobile technology, video, and young adults
Asperger’s syndromeEmotion recognition, attention deficit hyperactivity disorder, experiences, pervasive developmental disorders, randomized controlled trial, social skills, and computer-assisted instruction
SkillsSocial robots, young children, joint attention, behavior, emotions, iPads, serious games, and social interaction

References

  1. Fusar-Poli, L.; Brondino, N.; Politi, P.; Aguglia, E. Missed diagnoses and misdiagnoses of adults with autism spectrum disorder. Eur. Arch. Psychiatry Clin. Neurosci. 2020, 1–12. [Google Scholar] [CrossRef]
  2. Lorah, E.R.; Karnes, A.; Miller, J.; Welch-Beardsley, J. Establishing Peer Manding in Young Children with Autism Using a Speech-Generating Device. J. Dev. Phys. Disabil. 2019, 31, 791–801. [Google Scholar] [CrossRef]
  3. Vásquez, B.; Del Sol, M. Neuronal Morphology in Autism Spectrum Disorder. Int. J. Morphol. 2020, 38, 1513–1518. [Google Scholar]
  4. Fernández-Prieto, M.; Moreira, C.; Cruz, S.; Campos, V.; Martínez-Regueiro, R.; Taboada, M.; Carracedo, A.; Sampaio, A. Executive Functioning: A Mediator Between Sensory Processing and Behaviour in Autism Spectrum Disorder. J. Autism Dev. Disord. 2020, 1–13. [Google Scholar] [CrossRef] [PubMed]
  5. Hofvander, B.; Bering, S.; Tärnhäll, A.; Wallinius, M.; Billstedt, E. Few Differences in the Externalizing and Criminal History of Young Violent Offenders with and Without Autism Spectrum Disorders. Front. Psychiatry 2019, 10, 1–8. [Google Scholar] [CrossRef]
  6. Adams, D.; Emerson, L.-M. The Impact of Anxiety in Children on the Autism Spectrum. J. Autism Dev. Disord. 2020, 1–12. [Google Scholar] [CrossRef]
  7. Li, Y.; Zhou, Z.; Chang, C.; Qian, L.; Li, C.; Xiao, T.; Xiao, X.; Chu, K.; Fang, H.; Ke, X. Anomalies in uncinate fasciculus development and social defects in preschoolers with autism spectrum disorder. BMC Psychiatry 2019, 19, 399. [Google Scholar] [CrossRef] [Green Version]
  8. Muskett, A.; Capriola-Hall, N.; Radtke, S.R.; Factor, R.; Scarpa, A. Repetitive behaviors in Autism Spectrum Disorder: Associations with depression and anxiety symptoms. Res. Autism Spectr. Disord. 2019, 68, 101449. [Google Scholar] [CrossRef]
  9. Sadler, K.M. Video Self-Modeling to Treat Aggression in Students Significantly Impacted by Autism Spectrum Disorder. J. Spec. Educ. Technol. 2019, 34, 215–225. [Google Scholar] [CrossRef]
  10. Escolano-Pérez, E.; Acero-Ferrero, M.; Herrero-Nivela, M.L. Improvement of Planning Skills in Children with Autism Spectrum Disorder after an Educational Intervention: A Study from a Mixed Methods Approach. Front. Psychol. 2019, 10, 2824. [Google Scholar] [CrossRef]
  11. Adams, C.; Gaile, J. Evaluation of a parent preference-based outcome measure after intensive communication intervention for children with social (pragmatic) communication disorder and high-functioning autism spectrum disorder. Res. Dev. Disabil. 2020, 105, 103752. [Google Scholar] [CrossRef] [PubMed]
  12. Zajic, M.; Solari, E.J.; McIntyre, N.S.; Lerro, L.; Mundy, P.C. Observing Visual Attention and Writing Behaviors During a Writing Assessment: Comparing Children with Autism Spectrum Disorder to Peers with Attention-Deficit/Hyperactivity Disorder and Typically Developing Peers. Autism Res. 2020, 61, 1–13. [Google Scholar] [CrossRef] [PubMed]
  13. Scott, K.E.; Kazazian, K.; Mann, R.S.; Möhrle, D.; Schormans, A.L.; Schmid, S.; Allman, B.L. Loss of Cntnap2 in the Rat Causes Autism-Related Alterations in Social Interactions, Stereotypic Behavior, and Sensory Processing. Autism Res. 2020, 13, 1698–1717. [Google Scholar] [CrossRef] [PubMed]
  14. Kopec, J.; Hagmann, C.; Shea, N.; Prawl, A.; Batkin, D.; Russo, N. Examining the Temporal Limits of Enhanced Visual Feature Detection in Children with Autism. Autism Res. 2020, 13, 1561–1572. [Google Scholar] [CrossRef] [PubMed]
  15. Bacon, A.; Beaman, P.; Liu, F. An Exploratory Study of Imagining Sounds and “Hearing” Music in Autism. J. Autism Dev. Disord. 2019, 50, 1123–1132. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  16. Kovarski, K.; Malvy, J.; Khanna, R.K.; Arsène, S.; Batty, M.; Latinus, M. Reduced visual evoked potential amplitude in autism spectrum disorder, a variability effect? Transl. Psychiatry 2019, 9, 341. [Google Scholar] [CrossRef] [Green Version]
  17. Masson, H.L.; De Beeck, H.O.; Boets, B. Reduced task-dependent modulation of functional network architecture for positive versus negative affective touch processing in autism spectrum disorders. NeuroImage 2020, 219, 117009. [Google Scholar] [CrossRef]
  18. Schwartz, S.; Wang, L.; Shinn-Cunningham, B.G.; Tager-Flusberg, H. Atypical Perception of Sounds in Minimally and Low Verbal Children and Adolescents with Autism as Revealed by Behavioral and Neural Measures. Autism Res. 2020, 13, 1718–1729. [Google Scholar] [CrossRef]
  19. Ardalan, A.; Assadi, A.H.; Surgent, O.J.; Travers, B.G. Whole-Body Movement during Videogame Play Distinguishes Youth with Autism from Youth with Typical Development. Sci. Rep. 2019, 9, 20094. [Google Scholar] [CrossRef]
  20. Pereira, J.A.; Sepulveda, P.; Rana, M.; Montalba, C.; Tejos, C.; Torres, R.; Sitaram, R.; Ruiz, S. Self-Regulation of the Fusiform Face Area in Autism Spectrum: A Feasibility Study with Real-Time fMRI Neurofeedback. Front. Hum. Neurosci. 2019, 13, 446. [Google Scholar] [CrossRef]
  21. Sulek, R.; Trembath, D.; Paynter, J.; Keen, D. Factors Influencing the Selection and Use of Strategies to Support Students with Autism in the Classroom. Int. J. Disabil. Dev. Educ. 2019, 1–17. [Google Scholar] [CrossRef]
  22. Babb, S.; Raulston, T.J.; McNaughton, D.; Lee, J.-Y.; Weintraub, R. The Effects of Social Skill Interventions for Adolescents with Autism: A Meta-Analysis. Remedial Spec. Educ. 2020, 1–15. [Google Scholar] [CrossRef]
  23. Mayes, S.D.; Waschbusch, D.A.; Calhoun, S.L.; Mattison, R.E. How Common are Academic Overachievement and Underachievement in Children with Autism or ADHD? J. Dev. Phys. Disabil. 2019, 32, 775–783. [Google Scholar] [CrossRef]
  24. Westeinde, A.V.; Cauvet, É.; Toro, R.; Kuja-Halkola, R.; Neufeld, J.; Mevel, K.; Bölte, S. Sex differences in brain structure: A twin study on restricted and repetitive behaviors in twin pairs with and without autism. Mol. Autism 2019, 11, 1–20. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  25. Schiavi, S.; Carbone, E.; Melancia, F.; Buzzelli, V.; Manduca, A.; Campolongo, P.; Pallottini, V.; Trezza, V. Perinatal supplementation with omega-3 fatty acids corrects the aberrant social and cognitive traits observed in a genetic model of autism based on FMR1 deletion in rats. Nutr. Neurosci. 2020, 1–14. [Google Scholar] [CrossRef] [PubMed]
  26. Kasilingam, N.; Waddington, H.; Van Der Meer, L. Early Intervention for Children with Autism Spectrum Disorder in New Zealand: What Children Get and What Parents Want. Int. J. Disabil. Dev. Educ. 2019, 1–17. [Google Scholar] [CrossRef]
  27. Tupou, J.; Waddington, H.; Sigafoos, J. Evaluation of a Brief Teacher Coaching Program for Delivering an Early Intervention Program to Preschoolers with Autism Spectrum Disorder. Infants Young Child. 2020, 33, 259–282. [Google Scholar] [CrossRef]
  28. Taheri, H.; Sotoodeh, M.S. Using video and live modelling to teach motor skill to children with autism spectrum disorder. Int. J. Incl. Educ. 2018, 23, 405–418. [Google Scholar] [CrossRef]
  29. Perez-Fuster, P.; Sevilla, J.; Herrera, G. Enhancing daily living skills in four adults with autism spectrum disorder through an embodied digital technology-mediated intervention. Res. Autism Spectr. Disord. 2019, 58, 54–67. [Google Scholar] [CrossRef]
  30. López-Belmonte, J.; Carmona-Serrano, N.; Pérez-Rivero, N.; Martínez-Melendo, E. La realidad aumentada como tecnología emergente para la mejora de indicadores en TEA. In Innovación Docente e Investigación Educativa en la Sociedad del Conocimiento; Hinojo, F.J., Trujillo, J.M., Sola, J.M., Alonso, S., Eds.; Dykinson: Madrid, Spain, 2020; pp. 425–438. (In Spanish) [Google Scholar]
  31. O’Brolchain, F.; Gordijn, B. Responsibility-Enhancing Assistive Technologies and People with Autism. Camb. Q. Healthc. Ethic. 2020, 29, 607–616. [Google Scholar] [CrossRef]
  32. Rezae, M.; Chen, N.; McMeekin, D.; Tan, T.; Krishna, A.; Lee, H. The evaluation of a mobile user interface for people on the autism spectrum: An eye movement study. Int. J. Hum. Comput. Stud. 2020, 142, 102462. [Google Scholar] [CrossRef]
  33. Howorth, S.K.; Rooks-Ellis, D.; Flanagan, S.; Ok, M.W. Augmented Reality Supporting Reading Skills of Students with Autism Spectrum Disorder. Interv. Sch. Clin. 2019, 55, 71–77. [Google Scholar] [CrossRef]
  34. Ke, F.; Moon, J.; Sokolikj, Z. Virtual Reality–Based Social Skills Training for Children With Autism Spectrum Disorder. J. Spec. Educ. Technol. 2020, 1–14. [Google Scholar] [CrossRef]
  35. Lorenzo, G.; Gómez-Puerta, M.; Arráez-Vera, G.; Lledó, A.L. Preliminary study of augmented reality as an instrument for improvement of social skills in children with autism spectrum disorder. Educ. Inf. Technol. 2019, 24, 181–204. [Google Scholar] [CrossRef]
  36. So, W.-C.; Cheng, C.-H.; Lam, W.-Y.; Wong, T.; Law, W.-W.; Huang, Y.; Ng, K.-C.; Tung, H.-C.; Wong, W. Robot-based play-drama intervention may improve the narrative abilities of Chinese-speaking preschoolers with autism spectrum disorder. Res. Dev. Disabil. 2019, 95, 103515. [Google Scholar] [CrossRef] [PubMed]
  37. Fage, C.; Consel, C.; Etchegoyhen, K.; Amestoy, A.; Bouvard, M.; Mazon, C.; Sauzéon, H. An emotion regulation app for school inclusion of children with ASD: Design principles and evaluation. Comput. Educ. 2019, 131, 1–21. [Google Scholar] [CrossRef]
  38. Carrero, K.M.; Fuller, M.C. Teaching Adolescents with Autism to Text Message Requests Using Video Prompting. J. Spec. Educ. Technol. 2019, 1–10. [Google Scholar] [CrossRef]
  39. Roberts-Yates, C.; Silvera-Tawil, D. Better Education Opportunities for Students with Autism and Intellectual Disabilities through Digital Technology. Int. J. Spec. Educ. 2019, 34, 197–210. [Google Scholar]
  40. Ghanouni, P.; Jarus, T.; Zwicker, J.G.; Lucyshyn, J. The Use of Technologies Among Individuals with Autism Spectrum Disorders: Barriers and Challenges. J. Spec. Educ. Technol. 2020, 35, 286–294. [Google Scholar] [CrossRef]
  41. Hinojo-Lucena, F.-J.; Dúo-Terrón, P.; Navas-Parejo, M.R.; Jiménez, C.R.; Moreno-Guerrero, A.-J. Scientific Performance and Mapping of the Term STEM in Education on the Web of Science. Sustainability 2020, 12, 2279. [Google Scholar] [CrossRef] [Green Version]
  42. Segura-Robles, A.; Guerrero, A.J.M.; Parra-González, M.E.; Belmonte, J.L. Review of Research Trends in Learning and the Internet in Higher Education. Soc. Sci. 2020, 9, 101. [Google Scholar] [CrossRef]
  43. Cobo, M.J.; López-Herrera, A.G.; Herrera-Viedma, E.; Herrera, F. Science mapping software tools: Review, analysis, and cooperative study among tools. J. Am. Soc. Inf. Sci. Technol. 2011, 62, 1382–1402. [Google Scholar] [CrossRef]
  44. López-Belmonte, J.; Moreno-Guerrero, A.-J.; Núñez, J.A.L.; Sánchez, S.P. Analysis of the Productive, Structural, and Dynamic Development of Augmented Reality in Higher Education Research on the Web of Science. Appl. Sci. 2019, 9, 5306. [Google Scholar] [CrossRef] [Green Version]
  45. Rodríguez-García, A.-M.; Belmonte, J.L.; Montoro, M.A.; Guerrero, A.J.M. Productive, Structural and Dynamic Study of the Concept of Sustainability in the Educational Field. Sustainability 2019, 11, 5613. [Google Scholar] [CrossRef] [Green Version]
  46. Leung, X.Y.; Sun, J.; Bai, B. Bibliometrics of social media research: A co-citation and co-word analysis. Int. J. Hosp. Manag. 2017, 66, 35–45. [Google Scholar] [CrossRef]
  47. Belmonte, J.L.; Parra-González, M.E.; Segura-Robles, A.; Sánchez, S.P. Scientific Mapping of Gamification in Web of Science. Eur. J. Investig. Health Psychol. Educ. 2020, 10, 832–847. [Google Scholar] [CrossRef]
  48. Martínez, M.A.; Cobo, M.J.; Herrera, M.; Herrera-Viedma, E. Analyzing the Scientific Evolution of Social Work Using Science Mapping. Res. Soc. Work. Pract. 2014, 25, 257–277. [Google Scholar] [CrossRef]
  49. Hirsch, J.E. An index to quantify an individual´s scientific research output. Proc. Natl. Acad. Sci. USA 2005, 102, 16569–16572. [Google Scholar] [CrossRef] [Green Version]
  50. Guerrero, A.J.M.; Gómez-García, G.; Belmonte, J.L.; Rodríguez-Jiménez, C. Internet Addiction in the Web of Science Database: A Review of the Literature with Scientific Mapping. Int. J. Environ. Res. Public Health 2020, 17, 2753. [Google Scholar] [CrossRef]
  51. López-Robles, J.-R.; Otegi-Olaso, J.; Porto-Gómez, I.; Cobo, M. 30 years of intelligence models in management and business: A bibliometric review. Int. J. Inf. Manag. 2019, 48, 22–38. [Google Scholar] [CrossRef]
  52. López-Belmonte, J.; Marín-Marín, J.A.; Soler-Costa, R.; Moreno-Guerrero, A.J. Arduino Advances in Web of Science. A Scientific Mapping of Literary Production. IEEE Access 2020, 8, 128674–128682. [Google Scholar] [CrossRef]
  53. Moral-Munoz, J.A.; Herrera-Viedma, E.; Espejo, A.S.; Cobo, M.J. Software tools for conducting bibliometric analysis in science: An up-to-date review. El Prof. Inf. 2020, 29, 1–20. [Google Scholar] [CrossRef] [Green Version]
  54. Guerrero, A.J.M.; Belmonte, J.L.; Marín-Marín, J.-A.; Soler-Costa, R. Scientific Development of Educational Artificial Intelligence in Web of Science. Future Internet 2020, 12, 124. [Google Scholar] [CrossRef]
  55. Núñez, J.A.L.; Belmonte, J.L.; Guerrero, A.J.M.; Navas-Parejo, M.R.; Hinojo-Lucena, F.-J. Education and Diet in the Scientific Literature: A Study of the Productive, Structural, and Dynamic Development in Web of Science. Sustainability 2020, 12, 4838. [Google Scholar] [CrossRef]
  56. Guerrero, A.J.M. Estudio bibliométrico de la producción científica en Web of Science: Formación Profesional y blended learning. Pixel-Bit 2019, 56, 149–168. (In Spanish) [Google Scholar] [CrossRef]
  57. Montero-Díaz, J.; Cobo, M.J.; Gutiérrez-Salcedo, M.; Segado-Boj, F.; Herrera-Viedma, E. Mapeo científico de la Categoría «Comunicación» en WoS (1980–2013). Comunicar 2018, 26, 81–91. (In Spanish) [Google Scholar] [CrossRef] [Green Version]
  58. Parra-González, M.E.; Segura-Robles, A.; Vicente-Bújez, M.-R.; Belmonte, J.L. Production Analysis and Scientific Mapping on Active Methodologies in Web of Science. Int. J. Emerg. Technol. Learn. 2020, 15, 71–86. [Google Scholar] [CrossRef]
  59. Herrera-Viedma, E.; López-Robles, J.-R.; Guallar, J.; Cobo, M.J. Global trends in coronavirus research at the time of Covid-19: A general bibliometric approach and content analysis using SciMAT. El Prof. Inf. 2020, 29, 11. [Google Scholar] [CrossRef]
  60. Callon, M.; Courtial, J.P.; Laville, F. Co-word analysis as a tool for describing the network of interactions between basic and technological research: The case of polymer chemsitry. Scientometrics 1991, 22, 155–205. [Google Scholar] [CrossRef]
  61. Belmonte, J.L.; Segura-Robles, A.; Guerrero, A.J.M.; Parra-González, M.E. Machine Learning and Big Data in the Impact Literature. A Bibliometric Review with Scientific Mapping in Web of Science. Symmetry 2020, 12, 495. [Google Scholar] [CrossRef] [Green Version]
Brainsci 10 00985 g001 550
Figure 1. Flowchart according to the PRISMA declaration.
Figure 1. Flowchart according to the PRISMA declaration.
Brainsci 10 00985 g001
Brainsci 10 00985 g002 550
Figure 2. Evolution of research volume.
Figure 2. Evolution of research volume.
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Brainsci 10 00985 g003 550
Figure 3. Continuity of keywords between contiguous intervals.
Figure 3. Continuity of keywords between contiguous intervals.
Brainsci 10 00985 g003
Brainsci 10 00985 g004a 550Brainsci 10 00985 g004b 550
Figure 4. ASD-TECH strategic diagram by h-index. (a) 1992–2012; (b) 2013–2016; (c) 2017–2019.
Figure 4. ASD-TECH strategic diagram by h-index. (a) 1992–2012; (b) 2013–2016; (c) 2017–2019.
Brainsci 10 00985 g004aBrainsci 10 00985 g004b
Brainsci 10 00985 g005 550
Figure 5. Thematic evolution by h-index.
Figure 5. Thematic evolution by h-index.
Brainsci 10 00985 g005
Brainsci 10 00985 g006 550
Figure 6. Strategic author diagram of the entire production.
Figure 6. Strategic author diagram of the entire production.
Brainsci 10 00985 g006
Table
Table 1. Production indicators and inclusion criteria.
Table 1. Production indicators and inclusion criteria.
ConfigurationValues
Analysis unitKeywords, authors, WoS
Frequency thresholdKeywords: P1 = (3), P2 = (4), P3 = (5)
Authors: PX = (4)
Network typeCo-occurrence
Co-occurrence union value thresholdKeywords: P1 = (2), P2 = (2), P3 = (2)
Authors: PX = (2)
Normalization measureEquivalence index: eij = cij2/root (ci–cj)
Clustering algorithmMaximum size: 9; minimum size: 3
Evolutionary measureJaccard index
Overlapping measureInclusion rate
Table
Table 2. Scientific languages of publications.
Table 2. Scientific languages of publications.
Languagesn
English1039
Spanish15
Table
Table 3. Areas of knowledge.
Table 3. Areas of knowledge.
Areas of Knowledgen
Rehabilitation216
Developmental psychology187
Special education176
Education, educational research101
Table
Table 4. Types of documents.
Table 4. Types of documents.
Type of Documentn
Article677
Proceedings paper259
Review104
Table
Table 5. Institutions.
Table 5. Institutions.
Denominationn
University of California38
Vanderbilt University37
University of North Carolina35
Pennsylvania Commonwealth System of Higher Education (PCSHE)31
Table
Table 6. Most prolific authors on the relationship between the terms “autism” and “technology” (ASD-TECH).
Table 6. Most prolific authors on the relationship between the terms “autism” and “technology” (ASD-TECH).
Authorsn
Sarkar, N.22
Parsons, S.20
Warren, Z.17
Table
Table 7. Sources of origin.
Table 7. Sources of origin.
Denominationn
Journal of Autism and Developmental Disorders66
Lecture Notes in Computer Science37
Research in Autism Spectrum Disorders26
Autism25
Journal of Special Education Technology25
Table
Table 8. Most productive countries in terms of ASD-TECH research.
Table 8. Most productive countries in terms of ASD-TECH research.
Countriesn
USA519
England109
Italy53
Australia49
Canada43
Table
Table 9. Most cited articles on ASD-TECH.
Table 9. Most cited articles on ASD-TECH.
ReferencesCitations
Klin, A.; Jones, W.; Schultz, R.; Volkmar, F.; Cohen, D. Visual fixation patterns during viewing of naturalistic social situations as predictors of social competence in individuals with autism. Archives Gen. Psychiatry 2001, 59, 809–816, doi:10.1001/archpsyc.59.9.8091137
Miles, J.H. Autism spectrum disorders-A genetics review. Genet. Med. 2011, 13, 278–294, doi:10.1097/GIM.0b013e3181ff67ba296
Horner, R.H.; Carr, E.G.; Strain, P.S.; Todd, A.W.; Reed, H.K. Problem behavior interventions for young children with autism: A research synthesis. J. Autism Dev. Disord. 2002, 32, 423–446, doi:10.1023/A:1020593922901275
Krumm, N.; O’Roak, B.J.; Shendure, J.; Eichler, E.E. A de novo convergence of autism genetics and molecular neuroscience. Trends Neurosci. 2014, 37, 65–105, doi:10.1016/j.tins.2013.11.005248
Table
Table 10. Thematic research on ASD-TECH.
Table 10. Thematic research on ASD-TECH.
1992–2012
DenominationWorksIndex hIndex gIndex hgIndex q2Citations
Children79387151.9459.135093
Young children12101210.9523.451008
Prevalence1099919.67741
Assistive technology119119.9520.78516
Intervention128108.9421.73489
Disabilities8686.939.17426
Abnormalities666624.62505
Communication9697.3516.43323
People7676.4819.6330
Assisted reproductive technology444411.49311
Social skills444415.36221
Copy number variation444412.65371
Telemedicine7464.914.7133
Participatory design4343.46638
Face222221.91361
2013–2016
DenominationWorksIndex hIndex gIndex hgIndex q2Citations
Intervention186334538.5436.783502
Virtual reality53223427.3529.661236
Developmental disabilities20132016.1221.93560
Daily living skills19121814.718365
Spectrum15111512.8514.83335
iPad15101411.8313.78260
Copy number variation15101411.8318.44617
Animated tutor119109.4919.21517
Adults199161215.59266
Behavior9686.938.49129
Genetics7676.488.8388
Assisted reproductive technology9586.3210124
Recognition544413.86170
Therapy5343.468.4957
Instruction43338.1264
2017–2019
DenominationWorksIndex hIndex gIndex hgIndex q2Citations
Children250131915.7215.3969
Skills388119.389.38158
Virtual reality21898.499.38109
Asperger’s syndrome177118.7710.9116
Daily living skills31697.358.12119
Assisted reproductive technology8586.328.66260
Applied behavioral analysis14586.326.3279
Disabilities15454.475.2943
Prevalence8464.96.6348
Communication16343.463.8734
Acquisition15343.463.8728
Risk6353.877.3551
Rett syndrome4343.464.2421
Anxiety4343.463.8723
Vocabulary3232.456.3225
Play5232.454.4719
Need311111
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Carmona-Serrano, N.; López-Belmonte, J.; Cuesta-Gómez, J.-L.; Moreno-Guerrero, A.-J. Documentary Analysis of the Scientific Literature on Autism and Technology in Web of Science. Brain Sci. 2020, 10, 985. https://doi.org/10.3390/brainsci10120985

AMA Style

Carmona-Serrano N, López-Belmonte J, Cuesta-Gómez J-L, Moreno-Guerrero A-J. Documentary Analysis of the Scientific Literature on Autism and Technology in Web of Science. Brain Sciences. 2020; 10(12):985. https://doi.org/10.3390/brainsci10120985

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Carmona-Serrano, Noemí, Jesús López-Belmonte, José-Luis Cuesta-Gómez, and Antonio-José Moreno-Guerrero. 2020. "Documentary Analysis of the Scientific Literature on Autism and Technology in Web of Science" Brain Sciences 10, no. 12: 985. https://doi.org/10.3390/brainsci10120985

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