Next Article in Journal
Prevalence and Determinants of Diarrhea, Fever, and Coexistence of Diarrhea and Fever in Children Under-Five in Bangladesh
Previous Article in Journal
Asymptomatic Infant Rib Fractures Are Primarily Non-abuse-Related and Should Not Be Used to Assess Physical Child Abuse
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Children
Volume 10
Issue 11
10.3390/children10111828
children-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

A Scoping Review of Studies on Assistive Technology Interventions and Their Impact on Individuals with Autism Spectrum Disorder in Arab Countries

by
Maha Al-Hendawi
1,*,
Esraa Hussein
1,
Badriya Al Ghafri
1 and
Sefa Bulut
2
1
Department of Psychological Sciences, College of Education, Qatar University, Doha P.O. Box 2713, Qatar
2
Department of Counseling Psychology, School of Education, Ibn Haldun University, 34494 İstanbul, Turkey
*
Author to whom correspondence should be addressed.
Children 2023, 10(11), 1828; https://doi.org/10.3390/children10111828
Submission received: 11 October 2023 / Revised: 13 November 2023 / Accepted: 17 November 2023 / Published: 20 November 2023
(This article belongs to the Section Pediatric Mental Health)
Browse Figures
Versions Notes

Abstract

:
The rising prevalence of autism spectrum disorder (ASD) in Arab countries necessitates evidence-based interventions. Assistive technology (AT) presents a promising approach. However, data on the pervasiveness of AT use and its effectiveness for individuals with ASD, specifically within Arab countries, remain scarce. Objective: To review the current literature on the AT interventions and outcomes reported for individuals with ASD in Arab countries. Methods: A scoping review adhering to PRISMA guidelines was undertaken to explore the utilization of AT, segmented into three categories: low-technology (low-tech), mid-technology (mid-tech), and high-technology (high-tech) devices. Results: Twelve studies had a pooled sample of 1547 participants, primarily male school-aged children with ASD. The AT applications evaluated ranged from low-tech visual schedules and support to high-tech virtual reality systems. Studies have reported the potential benefits of AT in improving communication, social, academic, adaptive, and functional abilities; however, comparative evidence between AT interventions is limited. The identified barriers to the adoption of AT included caregiver uncertainty about the use of AT and a lack of awareness of AT among professionals and the Arab community in general. Conclusion: Available studies suggest that the adoption of AT can enhance the skills of individuals with ASD in Arab countries. However, more rigorous studies across diverse demographic groups and Arab national regions are needed to strengthen the evidence base and provide appropriate recommendations.

1. Introduction

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by persistent social interactions and communication challenges, accompanied by repetitive behaviors that manifest in the early developmental period [1,2,3,4]. The complex and heterogeneous symptoms and behaviors associated with ASD require an early and accurate diagnosis, as well as the timely implementation of evidence-based interventions to improve developmental outcomes. This is particularly critical in regions with limited healthcare resources and public awareness of ASD.
Assistive technology (AT) encompasses a wide range of low-tech and high-tech aids, including visual support, social narratives, speech-generating devices, video modeling, and mobile technologies [5]. AT has been shown to be effective in supporting children with ASD in various settings and developmental domains [6,7,8]. Studies have shown that AT can facilitate engagement, learning, communication, and the inclusion of children with ASD in home, school, and community environments [9,10,11]. International conventions affirm access to appropriate AT as a human right for individuals with disabilities. A growing body of evidence indicates that AT can enhance functional skills critical to independence and participation in children with ASD. For example, research shows that communication aids, such as picture exchange systems, can improve language abilities, reduce sensory issues, and build social interaction skills [12,13,14].
The prevalence of ASD has increased worldwide and this trend is mirrored in the Arab world [12,13,14]. Salhia et al. (2014) examined the epidemiological landscape of ASD in Arab Gulf countries, revealing a prevalence range of 1.4 to 29 cases per 10,000 individuals and identifying potential metabolic, autoimmune, and environmental risk factors [15]. In Qatar, a prevalence of 1.14% was reported among school-aged children between 2015 and 2018 [2]. Furthermore, the World Population Review reported a high prevalence of ASD in Arab countries such as Qatar (151.2/10,000 or 1 in 66), the United Arab Emirates (UAE) (1 in 89), Oman (1 in 93), Bahrain (1 in 97), and Saudi Arabia (1 in 99), highlighting the need for early diagnosis and effective intervention [16].
The increase in the prevalence of ASD has led to a greater focus on interventions and the use of AT [8,17,18]. The effective implementation of interventions such as AT is often intertwined with the sociocultural and infrastructure dynamics of a region, emphasizing the importance of examining its adoption and results in Arab countries to accurately assess its impact [1,6,19,20]. Specifically, the recognized potential of AT to improve functional outcomes calls for an understanding of its impact within the Arab context, unveiling region-specific benefits and challenges, and assisting in devising effective implementation strategies. This aligns with the global recognition of access to AT as a human right, advocating the need to explore its prevalence and outcomes in diverse regions to foster global equity in access to AT and its benefits [8,17,18].
This review used a scoping framework to synthesize existing evidence on AT interventions for people with ASD in Arab countries [21]. Using this framework allows for a comprehensive synthesis of the available research evidence to determine the extent, range, and nature of evidence on the use of AT in ASD within the Arab sociocultural context. This scoping review methodology facilitated the resolution of the broad research questions underpinning this study.
1.
What types of AT tools have been examined in studies conducted in Arab countries?
2.
What outcomes have been reported when AT is used with people with ASD in Arab countries?
3.
What factors influence AT adoption by people with ASD in Arab countries?

2. Methodology

2.1. Literature Search Strategy

A comprehensive literature search was conducted to examine the use of AT by individuals with ASD in Arab countries using a scoping review framework [21]. Electronic databases PubMed, ERIC, Education Source, Education Database, PsycArticles, Academic Search Ultimate, Psychology Database, and Taylor and Francis Online were systematically searched. The search was limited to articles published in English in peer-reviewed journals from 1 January 2013 to 31 December 2023.
The search strategy employed the keywords “Autism” and “Technology,” along with either “Arab” or “Middle East.” These keywords were derived following a meticulous examination of titles, abstracts, and terms within articles previously identified as pertinent and by evaluating the outcomes of exploratory searches.
The settings for AT interventions included in this review were categorized as specialized autism centers, educational settings, and diverse environments. Specialized autism centers provide customized interventions and education for individuals with ASD using evidence-based practices. Educational settings included mainstream and special education schools attended by students with ASD. Diverse settings refer to various other environments, such as homes, community spaces, vocational sites, and clinics, where assistive technology use has been studied.

2.1.1. Inclusion Criteria

The inclusion in this review was based on five distinct criteria: (a) articles must be in English and peer-reviewed, (b) publication dates between 2013 and 2023, (c) a focus on Arab individuals diagnosed with ASD, (d) involvement of AT tools, and (e) studies conducted in diverse settings, including schools, homes, and other relevant environments. Exclusion criteria encompassed studies published in books, book chapters, and conference papers.

2.1.2. Screening and Study Selection

The abstract of each identified article was independently screened by two reviewers and marked as Yes (Y) or No (N) in the corresponding columns of the spreadsheet, indicating whether it met each of the five predetermined inclusion criteria. Only articles for which both reviewers marked Yes for all inclusion criteria were reviewed and analyzed in the full text. For abstracts lacking sufficient information to determine eligibility, the two reviewers briefly reviewed the full text to reach a consensus on whether the inclusion criteria were met. Inter-rater reliability was established by having the two reviewers independently code a random 30% sample (n = 559) of the abstracts initially selected, achieving a high agreement rate of 94%. Any coding discrepancies were resolved through discussions between the reviewers until a consensus was reached. This rigorous systematic screening ensured that the included studies accurately represented the target population, interventions, comparators, and outcomes.

2.1.3. Definition and Types of AT

AT refers to any device, equipment, or system that aims to maintain or improve the functional capabilities of people with disabilities. AT supports skill development and enhances opportunities for children with disabilities through interventions, training, and technical guidance [22]. AT is commonly classified as low-, mid-, or high-tech based on its features and training needs [23]. Low-tech devices are non-electronic, simple, and customizable aids such as visual schedules, sensory tools, and adapted utensils (Table 1). They require minimal training to use and are inexpensive [24,25]. Mid-tech refers to basic electronic devices such as audio recorders, screen readers, and switch-adapted toys, bridging low-tech and advanced options. High-tech devices are sophisticated electronic technologies such as speech-generating devices, virtual reality platforms, and robotic systems. They enable personalized support but can be complex and costly [26].

2.1.4. Assessment of Risk of Bias

Selection bias was evaluated in the reviewed studies based on the sampling methods and group comparability. The widespread use of convenience sampling in most studies indicated a high risk of selection bias. Performance bias was gauged by examining the blinding of participants and researchers; however, the lack of reported blinding in most studies indicated a high risk in this area. Detection bias was considered based on whether the outcome assessors were blinded or not. However, many studies did not detail the blinding procedures, suggesting a possible risk of detection bias. Attrition bias was determined by examining the completeness of the outcome data, with most studies showing low dropout rates, indicating a low risk of attrition bias. Reporting bias was assessed in terms of the selective reporting of results. The absence of preregistered protocols in many studies suggested a potential risk of reporting bias.

2.1.5. Data Extraction and Synthesis

A structured data extraction process was developed to systematically review and synthesize the relevant information from the included articles. A customized Excel worksheet was created to capture key data points, with columns for the type of AT, publication year, study design, outcomes evaluated, country, setting, and age and gender of the participant. A descriptive analysis of the extracted data was performed using STATA statistical software version 18 to synthesize the results of all the studies and summarize the evidence. Frequencies and percentages were calculated for categorical variables such as type of AT, country, setting, and demographics of the participants. For continuous variables, means and standard deviations or medians and ranges were calculated as appropriate.

3. Results

3.1. Study Selection

Initial database searches identified 1865 records after removing duplicates (Figure 1). Two independent reviewers screened the titles and abstracts of these records against predefined eligibility criteria. A total of 1834 records were excluded because they were irrelevant because they did not focus on individuals with ASD (n = 1456), did not investigate AT (n = 256), or were not conducted in Arab countries (n = 122). The full-text articles of the remaining 31 records were retrieved and formally assessed for eligibility by two reviewers. Of these 31 articles, 19 were excluded for the following reasons: not being peer-reviewed journal articles (n = 5), published in languages other than English (n = 3), not assessing AT interventions (n = 6), had outcomes unrelated to AT use (n = 3), and included children without ASD diagnoses (n = 2). After these screening stages, 12 studies satisfied all the inclusion criteria and were included in the qualitative synthesis for this review. In total, 12 studies met the eligibility criteria and were included in this scoping review (Table 2).
The bias assessment of the 12 included studies indicated a high risk of selection bias in 11 studies (91.7%) stemming from the predominant use of convenience sampling methods without comparability between groups (Table 3). All studies (12 studies, 100%) also had a high risk of performance bias because blinding of participants and researchers was not commonly reported. Detection bias was unclear in 1 study (8%) and high in 5 studies (41.7%) as blinding of outcome assessors was frequently not described. However, all studies (12 studies, 100%) had a low risk of attrition bias, with reasonably complete outcome data and minimal dropouts. Finally, all studies had an unclear (1 study, 8%) or high risk of reporting bias as preregistered protocols were rarely used and selective reporting of results could not be ruled out.

3.2. Key Pooled Findings

The included studies had sample sizes ranging from 3 to 1168 participants, comprising mainly children but some adults up to 26 years of age (Table 2). There was a greater representation of male participants than female participants in most studies where gender was reported. Various study designs were used, including single-case experiments [29,33,34], surveys [22,27], randomized controlled trials [32], and qualitative methods [36]. Studies examined a range of ATs, from low-tech adaptations to high-tech virtual reality systems. Studies indicated the potential benefits of AT in improving abilities in areas such as communication [22,32], social skills [29,34], academic performance [36], and cultural knowledge [33]. Studies also provided information on caregiver and teacher awareness and perspectives on technological use [22,27].

3.3. Regional and Type Distribution

Most studies were carried out in the Gulf countries, including seven from the UAE [29,30,31,32,33,34,35,36], one from Qatar [27], and two from Saudi Arabia (KSA) [1,28]. One such study was conducted in Jordan [36]. One study included researchers from Qatar, the UAE, and the USA [37]. Figure 2A illustrates the geographical distribution of the studies within the Arab region and Figure 2B presents the types of AT used in these studies.

3.4. Research Settings

The studies examined were categorized into three distinct settings: specialized autism centers, educational settings, and diverse settings.
In the first category, specialized autism, three and four studies were conducted in controlled environments that were overlooked by experts [30,32,36]. For example, Fteiha (2017) conducted a study at the Dubai Autism Center, where participants were divided into three groups [32]. The first experimental group engaged with the CompuThera program to enhance reading proficiency, the second group engaged with the Language Master program to improve reading abilities, and the control group received conventional language training. The second category, educational settings, encompassed four studies conducted in school environments that promoted a sense of familiarity and comfort among participants [27,29,33,35]. A notable aspect of this setting was the designated resource room used for assessments, which ensured a consistent environment. Assessments were performed by qualified educators to maintain methodological rigor.
The third category, diverse settings, included studies conducted in various settings. For instance, Safi et al. (2021) [34] conducted their study in participants’ homes [28] and Borgestig et al. (2021) [31] conducted their study in both school and home settings [31]. Cabibihan et al. focused on different advanced ATs from the perspective of sensing technologies [35]. Additionally, some studies, such as Alsari et al. (2020) [28] and Alabbas and Miller (2019) [22], utilized virtual environments through online platforms and social media to engage a broader research sample, including community members, healthcare professionals, and augmentative and alternative communication (AAC) users [22,37].

3.5. Participant Characteristics

Most studies showed a higher number of male participants than female participants, as observed in previous studies [22,29,30,33,34]. The age range of the participants varied widely, with the youngest being 1 year old in the study by Alabbas and Miller (2019) [22] and the oldest being 26 in the study by Borgestig et al. (2021) [31]. One study included participants aged ≥18 years without specifying an upper age limit [38].

3.6. Sensory Technology and Outcome

An analysis of the selected articles revealed distinctions in terms of sensory technology, specifically visual and audiovisual technology (Figure 3A). Six studies focused on visual technology [28,30,31,33,34,35]. Two studies focused on audiovisual technology [28,36]. Four studies [22,27,32,37] did not specify a specific AT category.
The outcomes were organized into two groups (Figure 3B): skill enhancement and awareness of AT utilization. Nine studies focused on enhancing various skills [22,30,31,32,33,34,35,36]. One study did not focus on specific outcomes [37]. Two studies [27,37] investigated awareness of the importance of AT for children with autism.

3.7. Technology Stage

These studies discussed the development and utilization of various technologies (Table 1 and Table 2). Studies of children with ASD and technology covered different stages, including technologies as potential products, products in development, and products in active use. The technological descriptions varied based on the research focus, ranging from detailed accounts of individual applications to specific technological solutions and more generic descriptions, resulting in a relatively general categorization of the types of technologies used.

3.8. Aims of Employing AT

The analysis of the selected studies revealed diverse objectives for utilizing AT in individuals with ASD. These purposes broadly fell into three major categories: exploring caregivers’ and teachers’ perspectives and awareness, diagnostic and early intervention strategies, and initiatives for skill enhancement.
Three distinct studies were identified in the first category: Alabbas and Miller (2019 [22]), Al-Attiyah et al. (2020 [27]), and Alsari et al. (2020 [28]), who utilized surveys to delve into the perceptions and awareness of caregivers and teachers regarding AT. These studies employed surveys to effectively address their research inquiries. Alabbas and Miller (2019) explored Saudi Arabian caregivers’ perceptions by surveying the problems they encountered with typical routines, the solutions they found to the problems, the AT they used in the solutions, and their training and feelings of competence in using AT. Al-Attiyah et al. (2020 [27]) utilized a survey to explore teachers’ perceptions about integrating AT into educational settings for children with disabilities. Alsari et al. (2020 [28]) developed and distributed a survey to obtain information on awareness, accessibility, and funding for AAC services and devices within the Kingdom of Saudi Arabia (KSA).
The second category included three studies that focused on diagnosis, with Siyam and Abdallah (2022 [35]) aiming for earlier diagnosis through mobile technology. Siyam and Abdallah (2022 [35]) focused on earlier diagnoses and investigated the use of mobile technology for the coordination of therapy and learning for students with disabilities. The third category encompassed ten studies on using AT to enhance abilities in individuals with ASD, including communication, social, academic, and daily living skills. For example, Alzyoudi et al. (2015 [29]) evaluated video modeling to improve social skills development, whereas Borgestig et al. (2021 [31]) and Fteiha (2017 [32]) investigated AT interventions to enhance communication abilities. Safi et al. (2021 [34]) explored virtual voice assistants for improving speech and social interaction skills. Sweidan et al. (2019) [36] developed a smartphone application to teach linguistic, mathematical, and social skills to Arabic-speaking children with ASD. Cabibihan et al. focused on sensing technologies in general [39]. Banire et al. (2015) [30] pursued developing a customized learning system framework to guide the creation of software tailored to autistic learners’ needs. Olsen et al. (2018) [33] utilized video modeling to teach culture-specific dressing skills to participants with ASD.

3.9. Types of AT

The reviewed studies employed a diverse range of AT tools categorized as mid-tech and high-tech interventions. Notably, high-tech devices were the most prominent in the Gulf region, with eight studies utilizing advanced technologies [28,30,31,34]. For example, in Saudi Arabia, Alsari et al. (2020) [28] distributed surveys via social media and email to collect AAC device usage data [37]. Given the high prevalence of communication disorders in the country, AAC’s nontechnological and high-tech tools for nonverbal communication are particularly crucial. Similarly, in the UAE, Alzyoudi et al. (2015) [29] used television video modeling as a high-tech social skills intervention for children with ASD [29]. Banire et al. (2015) developed a computer-based learning system to teach Quran recitation while sustaining attention [30]. In a multicenter study, Borgestig et al. (2021) used eye-gaze-controlled computers to enhance communication and engagement [31]. Expanding beyond the Gulf, Sweidan et al. (2019) created a smartphone app in Jordan to teach linguistic, mathematical, and social skills through interactive games and activities [36]. Siyam and Abdallah (2022) investigated mobile technology to coordinate educational plans and underscore participatory design principles in the UAE [35]. Other reviewed studies focused on interventions such as video modeling for teaching culture-specific skills [33], virtual voice assistants for improving speech and social abilities [28], and computer programs for building language competencies [32].

3.10. Effectiveness of Using AT

Several studies demonstrated the potential of AT in enhancing social skills in individuals with ASD [29,31,34,36]. Virtual voice assistants improved vocabulary, phrase production, and social interaction compared to traditional therapies in three children [34]. An Android app was most effective for mild-to-moderate ASD when used for limited durations under supervision [36]. Eye gaze technology increased expressive communication in 17 participants with complex needs [31].
Two studies showed a positive impact of AT on cognitive and language skills. Hybrid visual learning systems increased attention span and on-task behaviors more than traditional teaching in children with ASD [30]. Language development software provided reinforcement and enhanced skills [32]. One study demonstrated that video modeling was an acceptable and effective method for teaching culture-specific dressing skills to Emirati children, which parents acknowledged as important [33]. Two surveys provided insights into stakeholder AT awareness and perspectives [27,28]. Caregivers frequently used technologies, but some experienced feelings of inadequacy in their use, in contrast to teachers who demonstrated high adoption proficiency and endorsed the benefits. Awareness of augmentative communication was higher among professionals than community members.

4. Discussion

This scoping review synthesized evidence from 12 studies on AT interventions for individuals with ASD in Arab countries. The key findings were that the AT tools were primarily aimed at communication, social, academic, and cultural skills. Most studies involved mid- to high-tech AT, likely reflecting the relatively advanced infrastructure in the Gulf countries where these studies were conducted. Only one randomized controlled trial demonstrated the efficacy of AT in improving language skills, and the majority of the evidence was derived from small observational studies. The reported outcomes included gains in communication, social interactions, academics, and cultural knowledge. High adoption was observed among teachers and caregivers, indicating an increasing mainstream acceptance of AT in Arab countries. However, disparities in awareness and cost and a lack of collaboration emerged as barriers to the widespread adoption of AT. These results are consistent with those of previous studies on the use of AT for people with intellectual disabilities and ASD [17,39].

4.1. Type of AT and Geographical Variation

The reviewed studies reflected a predominance of mid- and high-tech AT, primarily in Gulf countries. This prevalence can be attributed to the relatively advanced economic and technological infrastructure of the Gulf countries, which allows for greater investment in sophisticated AT solutions compared to other Arab countries with limited resources [19]. In low-income countries, the widespread availability of high-tech and mid-tech AT may be limited, especially for impoverished citizens [26]. In contrast, low-tech assistive devices tend to see a higher adoption owing to their cost-effectiveness, simpler mechanics, and minimal training requirements [24,40]. It should be noted that low-tech AT can be made by families without requiring specialist input; for example, homemade supports such as rolled towels for sitting aids and weighted utensils to facilitate feeding exemplify the adaptability of low-tech solutions [41]. Such ingenuity in using readily available materials can enhance a child’s engagement in natural family settings and surroundings. However, making a decisive remark on the efficacy of different types of ATs is challenging due to the absence of comparative evidence evaluating the differential efficacy of various types of AT within the Arab region. In particular, this lack of rigorous comparative research is not confined to the Arab region but is a global issue, indicating the urgent need for more extensive research on the comparative evaluation of a wide range of AT tools and technologies [17].

4.2. Impact of AT on Outcomes

The reported results included improved communication skills, social skills, academics, and cultural knowledge. Our analysis found only one randomized controlled trial on the use of AT for ASD [32]. It involved 12 children and found that AT effectively improved language skills in autism. As noted above, previous research has also shown positive effects of AT on communication abilities, including mutual attention, verbal skills, imitation, and stereotypical reduction [17,39]. Specifically, a review by Syriopoulou-Delli and Gkiolnta analyzed 13 studies on AT in children with ASD and found positive immediate effects on communication skills such as mutual attention, verbal skills, and imitation, as well as reduced stereotypy [39]. Similarly, Maseri et al. analyzed 15 studies, revealing that autism-assistive apps improve verbal communication abilities in children with ASD [17]. Another key finding of our review was the association between AT use and improved social interaction in multiple studies. Technologies, such as virtual assistants and autism applications, promote social engagement and communication skills [28,34], confirming the results of other studies on the potential of AT to address ASD social communication challenges [5,7,17,18].
Importantly, AT affects cognitive and language skills more than cognitive skills alone. The CompuThera program [32], autism apps [36], and visual hybrid development learning systems [30] have improved these abilities, highlighting the adaptability and learning enablements of AT. A multicenter study demonstrated the benefits of eye-gaze-controlled computers [31], providing empirical evidence for AT and emphasizing multidisciplinary implementation. These positive outcomes demonstrate the versatility of AT and the potential for customized interventions that meet the unique learning needs of ASD. Overall, evidence indicates that thoughtfully designed technology tools aligned with areas of difficulty in autism spectrum disorder can create opportunities for greater social connection, relationship building, and participation. By supporting autistic learning styles and offering individualized scaffolding, assistive technology shows promise in improving real-world social interaction abilities and fostering greater involvement in children with autism spectrum disorder.

4.3. Adoption and Barriers

The high adoption among early intervention teachers [27] and caregiver use in daily routines [22] indicate a positive trajectory toward mainstream TA in educational and home settings. The use of mobile technology to coordinate educational plans [35] demonstrates the potential of AT to improve coordination and monitoring in inclusive classrooms, ensuring continuous assessment and adaptation to evolving student needs. Caregiver uncertainty, disparity between professional and public awareness, and low acceptance have emerged as critical barriers to the adoption of AT [1,22,28,42], reflecting the global challenges encountered in its implementation [17,38,43]. These findings imply that collaboration between speech therapists, occupational therapists, and other experts is integral to fully utilizing AT to address the diverse needs of patients with ASD. The high use of assistive technology among teachers [27] and caregivers [22] indicates the growing mainstream acceptance of these tools in Arab countries. This positive trajectory toward integrating assistive technology into standard educational and home settings for individuals with autism spectrum disorder can be further encouraged through comprehensive competency-building and training programs for stakeholders such as educators, therapists, and family members [1,22,28,44]. Addressing knowledge deficiencies and attitudinal barriers that impede wider assistive technology adoption through greater awareness and improved access to evidence of its benefits is also key to maximizing acceptance and uptake [1,22,28,44]. With dedicated efforts to build stakeholder capabilities and understanding of assistive technology, the mainstream integration of these beneficial tools into regular practice for individuals with autism spectrum disorder in Arab countries can be accelerated.

4.4. Age Diversity

Most studies focused on children, with minimal evidence of the effectiveness of AT across other age groups. However, ASD symptoms manifest differently across various developmental stages, resulting in changing support requirements over one’s lifespan [37]. For example, an assistive technology intervention focused on learning social skills may be suitable for a young child, whereas an adult may benefit more from technology aids in gaining employment or independent living skills. Examining tailored assistive technology strategies for youth, mature adults, and elderly people with autism spectrum disorder will offer insights into optimizing the benefits across age groups. Taking a lifespan developmental approach to study assistive technology interventions for individuals with autism spectrum disorder will be key to ensuring that these tools can improve outcomes and enhance functioning at all ages.

4.5. Knowledge Gaps and Implications for Future Research

The 12 included studies identified several key factors affecting the use of AT for ASD in the Arab region. However, significant knowledge gaps persist. More controlled clinical trials are critical to guide the appropriate and equitable adoption of the immense potential of AT to improve ASD outcomes in Arab countries and worldwide. Moreover, with regard to AT types, visual and audiovisual technologies have been the most studied, whereas research on other options of sensory approaches remains limited. This is despite the well-known sensory processing challenges present in populations with ASD, suggesting a mismatch between current AT priorities and user needs [37,44]. The diverse range of technologies adopted in these studies, from concepts to active tools, indicates the need to standardize development, evaluation, and implementation [45]. More research is necessary in naturalistic home and community settings where social inclusion is the goal [3]. These nurturing-regulated environments accommodate the unique requirements of students with ASD, thereby enhancing their potential and development [46]. Most research has focused on children. However, AT use lacks fixed age boundaries in ASD, likely owing to ASD’s varying manifestations across ages and phases, contributing to evolving needs [47]. Addressing age diversity will provide insights into tailoring AT to meet ASD demands across age groups. Addressing stakeholder competencies and attitudinal gaps may promote their adoption. Small samples and reliance on surveys rather than robust experiments also introduce bias. Addressing these limitations through rigorous, diverse, and extensive research is essential to firmly guide evidence-based practice.

4.6. Limitations

This review has several limitations that restrict the generalizability of the findings regarding the use of AT for ASD in Arab countries. The small sample sizes and reliance on surveys and observational studies rather than controlled experiments introduce a potential bias. Most studies focused on children, with limited evidence across age groups. There was also greater emphasis on visual and audio AT interventions than on other sensory modalities.

5. Conclusions and Future Directions

This scoping review underscores the potential benefits but provides limited evidence of AT for children with ASD in the Middle East. Preliminary studies have revealed promising outcomes for communication, academic, adaptive, and social skills. However, substantial gaps exist, including a lack of data on the perspectives of families and individuals with ASD and minimal research on low-tech solutions to improve accessibility. Rigorously designed studies that compare AT with standard practices are urgently required. Implementation research should identify optimized training, support, and capacity-building models for the sustainable use of AT in educational and clinical contexts. Policy and advocacy initiatives must address funding, infrastructure, and attitudinal barriers that inhibit access. This review highlights critical steps for strengthening the evidence base through expanded, rigorous research and simultaneous efforts to enhance equitable access and capacity surrounding AT. Key priorities include increasing stakeholder participation, improving methodological quality, and focusing on functional and participatory outcomes. Collaborative dedication among researchers, practitioners, policymakers, and the autism community is essential for realizing the full benefits of AT.

Author Contributions

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

Funding

This research was funded by Qatar University (QUCP-CED-2021-2). The findings herein are solely the responsibility of the author.

Institutional Review Board Statement

This study did not involve human subjects or related data. Thus, institutional review board approval was not sought.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Alallawi, B.; Hastings, R.P.; Gray, G. A Systematic Scoping Review of Social, Educational, and Psychological Research on Individuals with Autism Spectrum Disorder and their Family Members in Arab Countries and Cultures. Rev. J. Autism Dev. Disord. 2020, 7, 364–382. [Google Scholar] [CrossRef]
  2. Alshaban, F.; Aldosari, M.; Al-Shammari, H.; El-Hag, S.; Ghazal, I.; Tolefat, M.; Ali, M.; Kamal, M.; Abdel Aati, N.; Abeidah, M.; et al. Prevalence and correlates of autism spectrum disorder in Qatar: A national study. J. Child Psychol. Psychiatry 2019, 60, 1254–1268. [Google Scholar] [CrossRef]
  3. Hussein, H.A.; Taha, G.R. Autism spectrum disorders: A review of the literature from Arab countries. Middle East. Curr. Psychiatry 2013, 20, 106–116. [Google Scholar]
  4. Hodges, H.; Fealko, C.; Soares, N. Autism spectrum disorder: Definition, epidemiology, causes, and clinical evaluation. Transl. Pediatr. 2020, 9, S55–S65. [Google Scholar] [CrossRef]
  5. Cañete, R.; Peralta, E. Assistive Technology to Improve Collaboration in Children with ASD: State-of-the-Art and Future Challenges in the Smart Products Sector. Sensors 2022, 22, 8321. [Google Scholar] [CrossRef]
  6. Valencia, K.; Rusu, C.; Quiñones, D.; Jamet, E. The Impact of Technology on People with Autism Spectrum Disorder: A Systematic Literature Review. Sensors 2019, 19, 4485. [Google Scholar] [CrossRef]
  7. Deng, L.; Rattadilok, P. The need for and barriers to using assistive technologies among individuals with Autism Spectrum Disorders in China. Assist. Technol. 2022, 34, 242–253. [Google Scholar]
  8. Boucenna, S.; Narzisi, A.; Tilmont, E.; Muratori, F.; Pioggia, G.; Cohen, D.; Chetouani, M. Interactive Technologies for Autistic Children: A Review. Cogn. Comput. 2014, 6, 722–774. [Google Scholar] [CrossRef]
  9. Bouck, E.C.; Long, H. Assistive Technology for Students with Disabilities: An Updated Snapshot. J. Spec. Educ. Technol. 2021, 36, 249–257. [Google Scholar] [CrossRef]
  10. Hughes, E.M.; Yakubova, G. Developing handheld video intervention for students with autism spectrum disorder. Interv. Sch. Clin. 2016, 52, 115–121. [Google Scholar]
  11. Kim, E.S.; Berkovits, L.D.; Bernier, E.P.; Leyzberg, D.; Shic, F.; Paul, R.; Scassellati, B. Social robots as embedded reinforcers of social behavior in children with autism. J. Autism Dev. Disord. 2013, 43, 1038–1049. [Google Scholar] [PubMed]
  12. Odom, S.L.; Thompson, J.L.; Hedges, S.; Boyd, B.A.; Dykstra, J.R.; Duda, M.A.; Szidon, K.L. Technology-aided interventions and instruction for adolescents with autism spectrum disorder. J. Autism Dev. Disord. 2015, 45, 3805–3819. [Google Scholar]
  13. Parsons, S.; Leonard, A.; Mitchell, P. Virtual environments for social skills training: Comments from two adolescents with autistic spectrum disorder. Comput. Educ. 2017, 50, 578–589. [Google Scholar] [CrossRef]
  14. Shane, H.C.; Albert, P.D. Electronic screen media for persons with autism spectrum disorders: Results of a survey. J. Autism Dev. Disord. 2008, 38, 1499–1508. [Google Scholar] [CrossRef]
  15. Salhia, H.O.; Al-Nasser, L.A.; Taher, L.S.; Al-Khathaami, A.M.; El-Metwally, A.A. Systemic review of the epidemiology of autism in Arab Gulf countries. Neurosciences 2014, 19, 291–296. [Google Scholar]
  16. Review, WP Autism Rates by Country 2023. 2023. Available online: https://worldpopulationreview.com/country-rankings/autism-rates-by-country (accessed on 1 September 2023).
  17. Maseri, M.; Mamat, M.; Yew, H.T.; Chekima, A. The Implementation of Application Software to Improve Verbal Communication in Children with Autism Spectrum Disorder: A Review. Children 2021, 8, 1001. [Google Scholar] [CrossRef]
  18. Lima Antão, J.Y.F.; Oliveira, A.S.B.; Almeida Barbosa, R.T.; Crocetta, T.B.; Guarnieri, R.; Arab, C.; Massetti, T.; Antunes, T.P.C.; Silva, A.P.D.; Bezerra, Ĺ.M.P.; et al. Instruments for augmentative and alternative communication for children with autism spectrum disorder: A systematic review. Clinics 2018, 73, e497. [Google Scholar] [CrossRef]
  19. Al Khateeb, J.M.; Kaczmarek, L.; Al Hadidi, M.S. Parents’ perceptions of raising children with autism spectrum disorders in the United States and Arab countries: A comparative review. Autism 2019, 23, 1645–1654. [Google Scholar] [CrossRef] [PubMed]
  20. Sulaimani, M. A Systematic Review of Autism Spectrum Disorder Research in the Arab World. J. Fac. Educ. 2023, 34, 53–72. [Google Scholar] [CrossRef]
  21. Daudt, H.M.L.; van Mossel, C.; Scott, S.J. Enhancing the scoping study methodology: A large, inter-professional team’s experience with Arksey and O’Malley’s framework. BMC Med. Res. Methodol. 2013, 13, 48. [Google Scholar] [CrossRef]
  22. Alabbas, N.A.; Miller, D.E. Challenges and Assistive Technology during Typical Routines: Perspectives of Caregivers of Children with Autism Spectrum Disorders and Other Disabilities. Int. J. Disabil. Dev. Educ. 2019, 66, 273–283. [Google Scholar] [CrossRef]
  23. Chambers, D. Assistive technology to enhance inclusive education. In Oxford Research Encyclopedia of Education; Oxford University Press: Oxford, UK, 2019. [Google Scholar] [CrossRef]
  24. Conderman, G. Assistive technologies: A lifeline for learning. Kappa Delta Pi Rec. 2015, 51, 173–178. [Google Scholar] [CrossRef]
  25. Jacobsen, D.L. Assistive Technology for Students with Disabilities: Resources and Challenges Encountered by Teachers. Ph.D. Thesis, University of Northern Lowa, Cedar Falls, IA, USA, 2012. [Google Scholar]
  26. Jadhav, V.; Chambers, D.; Tatpuje, D. Low-tech Assistive Technology to Support Students with Disability in Low-income Countries. Assist. Technol. Support Incl. Educ. 2020, 14, 37–50. [Google Scholar] [CrossRef]
  27. Al-Attiyah, A.A.; Dababneh, K.; Hamaidi, D.A.; Arouri, Y. Employing assistive technologies in teaching children with disabilities in early childhood settings: Teachers’ perceptions. Int. J. Early Years Educ. 2020, 30, 419–433. [Google Scholar] [CrossRef]
  28. Alsari, N.A.M.; Alshair, A.M.; Almalik, S.A.; Alsa’ad, S.S. A survey on the awareness, accessibility and funding for augmentative and alternative communication services and devices in Saudi Arabia. Disabil. Rehabil. Assist. Technol. 2020, 16, 789–795. [Google Scholar] [CrossRef]
  29. Alzyoudi, M.; Sartawi, A.; Almuhiri, O. The impact of video modelling on improving social skills in children with autism. Br. J. Spec. Educ. 2014, 42, 53–68. [Google Scholar] [CrossRef]
  30. Banire, B.; Jomhari, N.; Ahmad, R. Visual Hybrid Development Learning System (VHDLS) framework for children with autism. J. Autism Dev. Disord. 2015, 45, 3069–3084. [Google Scholar] [CrossRef]
  31. Borgestig, M.; Al Khatib, I.; Masayko, S.; Hemmingsson, H. The Impact of Eye-gaze Controlled Computer on Communication and Functional Independence in Children and Young People with Complex Needs—A Multicenter Intervention Study. Dev. Neurorehabilit. 2021, 24, 511–524. [Google Scholar] [CrossRef]
  32. Fteiha, M.A. Effectiveness of assistive technology in enhancing language skills for children with autism. Int. J. Dev. Disabil. 2016, 63, 36–44. [Google Scholar] [CrossRef]
  33. Olsen, P.M.; Bailey, L.S.; Gould, D.D. Using video modelling to teach culture-specific dressing skills. Eur. J. Behav. Anal. 2018, 19, 247–259. [Google Scholar] [CrossRef]
  34. Safi, M.F.; Al Sadrani, B.; Mustafa, A. Virtual voice assistant applications improved expressive verbal abilities and social interactions in children with autism spectrum disorder: A Single-Subject experimental study. Int. J. Dev. Disabil. 2021, 69, 555–567. [Google Scholar] [CrossRef] [PubMed]
  35. Siyam, N.; Abdallah, S. A Pilot Study Investigating the Use of Mobile Technology for Coordinating Educational Plans in Inclusive Settings. J. Spec. Educ. Technol. 2022, 37, 455–468. [Google Scholar] [CrossRef]
  36. Sweidan, S.Z.; Salameh, H.; Zakarneh, R.; Darabkh, K.A. Autistic Innovative Assistant (AIA): An Android application for Arabic autism children. Interact. Learn. Environ. 2019, 30, 735–758. [Google Scholar] [CrossRef]
  37. Cabibihan, J.-J.; Javed, H.; Aldosari, M.; Frazier, T.W.; Elbashir, H. Sensing Technologies for Autism Spectrum Disorder Screening and Intervention. Sensors 2017, 17, 46. [Google Scholar] [CrossRef]
  38. DiPietro, J.; Kelemen, A.; Liang, Y.; Sik-Lanyi, C. Computer- and Robot-Assisted Therapies to Aid Social and Intellectual Functioning of Children with Autism Spectrum Disorder. Medicina 2019, 55, 440. [Google Scholar] [CrossRef]
  39. Syriopoulou-Delli, C.K.; Gkiolnta, E. Review of assistive technology in the training of children with autism spectrum disorders. Int. J. Dev. Disabil. 2022, 68, 73–85. [Google Scholar] [CrossRef]
  40. Shaw, A. Low tech tools of empowerment: Accessing curriculum through assistive technology. Except. Parent. 2016, 46, 40–42. [Google Scholar]
  41. Guidance, C.P. Assistive Technology and Adaptive Equipment for Children with Cerebral Palsy. 2020. Available online: https://www.cerebralpalsyguidance.com/cerebral-palsy/living/assistive-technology/ (accessed on 1 September 2023).
  42. Alkhateeb, J.M.; Hadidi, M.S.; Mounzer, W. The Impact of Autism Spectrum Disorder on Parents in Arab Countries: A Systematic Literature Review. Front. Psychol. 2022, 13, 955442. [Google Scholar] [CrossRef]
  43. Quintana, G.R.; Mac Cionnaith, C.E.; Pfaus, J.G. Behavioral, Neural, and Molecular Mechanisms of Conditioned Mate Preference: The Role of Opioids and First Experiences of Sexual Reward. Int. J. Mol. Sci. 2022, 23, 8928. [Google Scholar] [CrossRef]
  44. Meilleur, A.; Foster, N.E.V.; Coll, S.-M.; Brambati, S.M.; Hyde, K.L. Unisensory and multisensory temporal processing in autism and dyslexia: A systematic review and meta-analysis. Neurosci. Biobehav. Rev. 2020, 116, 44–63. [Google Scholar] [CrossRef]
  45. Wainer, A.L.; Ingersoll, B. The use of innovative computer technology for teaching social communication to individuals with autism spectrum disorders. Res. Autism Spectr. Disord. 2011, 5, 96–107. [Google Scholar] [CrossRef]
  46. Murray, J. Practical Teaching Strategies for Students with Autism Spectrum Disorder: A Review of the Literature. BU J. Grad. Stud. Educ. 2015, 7, 68–75. [Google Scholar]
  47. Masi, A.; DeMayo, M.M.; Glozier, N.; Guastella, A.J. An overview of autism spectrum disorder, heterogeneity and treatment options. Neurosci. Bull. 2017, 33, 183–193. [Google Scholar] [CrossRef] [PubMed]
Children 10 01828 g001
Figure 1. Prisma flow chart.
Figure 1. Prisma flow chart.
Children 10 01828 g001
Children 10 01828 g002
Figure 2. Geographical distribution of studies in the Arab region and Distribution of AT types (N = 11).
Figure 2. Geographical distribution of studies in the Arab region and Distribution of AT types (N = 11).
Children 10 01828 g002
Children 10 01828 g003
Figure 3. (A) Type of AT (N = 11). (B) Outcome (N = 11).
Figure 3. (A) Type of AT (N = 11). (B) Outcome (N = 11).
Children 10 01828 g003
Table 1. Classification of AT.
Table 1. Classification of AT.
CategoryDescriptionExamplesCostTraining NeededBenefits
Low-TechSimple non-electronic aids to enhance skills. Highly customizable.Visual schedules, adapted utensils, sensory tools.Low (under $50)Minimal to noneProvides structure, makes tasks simpler.
Mid-TechElectronic devices/software to increase access to curricula. Require basic skills.Audiobooks, adapted keyboards, speech-to-text.Low to moderate ($100–$1000)Basic device training often needed.Allows greater independence for academic work.
High-TechSophisticated electronic systems requiring extensive training and customization.Speech-generating devices, virtual reality, robotics.High (over $1000)Extensive professional training required.Provides personalized, intensive support tailored to individual needs.
Actual costs and features of devices may vary. Details provided are tentative.
Table 2. Summary of key characteristics of included studies.
Table 2. Summary of key characteristics of included studies.
StudyCountryAge and Sample SizeIntervention and Outcome MeasuresTechnology UsedKey Results
(Alabbas and Miller, 2019 [22])Saudi Arabia1–5 year; N = 41Assistive technology; Daily routines; QualitativeOnline surveyHigh % of ASD and routine problems reported; AT most used for bathing and playing.
(Al-Attiyah et al., 2020 [27])QatarN = 183Assistive technologies; Teacher perceptions; Quantitative; DescriptiveAssistive technologiesHigh AT use by teachers.
(Alsari et al., 2020 [28])Saudi Arabia18 y or above; N = 1168AAC services and devices; AAC awareness; Access, Funding; QuantitativeAAC high-tech devicesSignificant difference in AAC awareness between groups.
(Alzyoudi et al., 2015 [29])UAE5–7 y; N = 5Video modeling; Social skills; Qualitative; Single subjectTV, videoEffective for improving social skills.
(Banire et al., 2015 [30])UAE5–7 y; N = 11Visual hybrid development learning system; Attention; Mixed methodsVisual hybrid Quran learning systemIncreased attention with VHDLS.
(Borgestig et al., 2021 [31])Sweden, UAE, USA3–26 y; N = 17Eye-gaze controlled computer; Communication; Functional independence; QuantitativeEGCCIncreased communication and functional independence.
(Fteiha, 2016 [32])UAE8–12 y; N = 12 AT computer programs; Language skills; Quantitative; Single subjectCompuTheraGreater language gains pre- to post-test.
(Olsen et al., 2018 [33])UAE7–15 y; N = 3Video modeling; Dressing skills; QualitativeComputerImproved dressing skills.
(Safi et al., 2021 [34])UAE4–11 y; N = 3Virtual voice assistants; Speech; Social interaction; Qualitative; Single caseApple SiriPositive effects on speech and social interaction.
(Siyam and Abdallah, 2022 [35])UAE6–10 y; N = 4 Mobile technology; IEP coordination; Qualitative; Participatory designMobile app (IEP-Connect)Good usability and satisfaction.
(Sweidan et al., 2019 [36])Jordan5–13 y; N = 100 Android app; Language; Math; Social skills; QuantitativeAndroid appMost improvement in Level 1; noticeable skill improvement.
(Cabibihan et al., 2017 [37])UAE, Qatar, USA-Sensing technologies; ASD screening and intervention; QualitativeSensing technologiesRoom for improvement remains in reliability and usability.
Table 3. Assessment of risk of bias in included studies.
Table 3. Assessment of risk of bias in included studies.
StudySelection BiasPerformance BiasDetection BiasAttrition BiasReporting Bias
Alabbas and Miller (2019 [22])HighHighUnclearLowUnclear
Al-Attiyah et al. (2020 [27])HighHighHighLowLow
Alsari et al. (2020 [28])HighHighLowLowLow
Alzyoudi et al. (2015 [29])HighHighHighLowLow
Banire et al. (2015 [30])HighHighLowLowLow
Borgestig et al. (2021 [31])LowHighLowLowLow
Fteiha (2016 [32])HighHighHighLowLow
Olsen et al. (2018 [33])HighHighHighLowLow
Safi et al. (2021 [34])HighHighLowLowLow
Siyam and Abdallah (2022 [35])HighHighLowLowLow
Sweidan et al. (2019 [36])HighHighLowLowLow
Cabibihan et al. (2017 [37])HighHighHighLowLow
Note: Selection bias was high in most studies due to convenience sampling. Performance bias risk was high as blinding of participants and researchers was mostly unreported. Detection bias also posed a potential risk due to unclear blinding of outcome assessors. Attrition bias was low, with most studies reporting low dropout rates. Finally, the lack of preregistered protocols in many studies suggested a possible risk of reporting bias.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Al-Hendawi, M.; Hussein, E.; Al Ghafri, B.; Bulut, S. A Scoping Review of Studies on Assistive Technology Interventions and Their Impact on Individuals with Autism Spectrum Disorder in Arab Countries. Children 2023, 10, 1828. https://doi.org/10.3390/children10111828

AMA Style

Al-Hendawi M, Hussein E, Al Ghafri B, Bulut S. A Scoping Review of Studies on Assistive Technology Interventions and Their Impact on Individuals with Autism Spectrum Disorder in Arab Countries. Children. 2023; 10(11):1828. https://doi.org/10.3390/children10111828

Chicago/Turabian Style

Al-Hendawi, Maha, Esraa Hussein, Badriya Al Ghafri, and Sefa Bulut. 2023. "A Scoping Review of Studies on Assistive Technology Interventions and Their Impact on Individuals with Autism Spectrum Disorder in Arab Countries" Children 10, no. 11: 1828. https://doi.org/10.3390/children10111828

APA Style

Al-Hendawi, M., Hussein, E., Al Ghafri, B., & Bulut, S. (2023). A Scoping Review of Studies on Assistive Technology Interventions and Their Impact on Individuals with Autism Spectrum Disorder in Arab Countries. Children, 10(11), 1828. https://doi.org/10.3390/children10111828

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop