INTRODUCTION
A neurodevelopmental illness known as autism spectrum disorder (ASD) is characterized by limitations in interests and repetitive activities, as well as difficulty in social communication [1]. About 1 in 36 children have been identified with ASD according to estimates from the American Centers for Disease Control and Preventions’ Autism and Developmental Disabilities Monitoring (ADDM) Network [2]. The average age of the first clinical diagnosis of ASD in the United States currently is 4.2 years [3]. Early intervention in the first years of life is critical, as the great brain plasticity at this stage allows the establishment and reorganization of neural networks in response to environmental stimulation [4]. The most crucial time for brain development is thought to be the first six years of life, during which time perceptual and motor skills, cognition, language and communication skills, and socioemotional skills are developed [5,6]. However, nearly half of children with the disease are not diagnosed until they are older than 6 years [3]. The aims of early intervention are to reduce ASD symptom severity, to prevent secondary (behavioral) problems, and to support family functioning to facilitate the acquisition of critical developmental skills and allow children to achieve independence across different environments [6,7]. Early intervention is beneficial to autistic children in various regards, including social functioning, adaptive behaviors, and behavioral regulation [8].
With the rapid development in information technology and telecommunication, medicine has been benefited immensely, and a new term “electronic health (e-health)” has emerged [9]. It is an emerging and rapidly growing field of medical research that involves the application of digital technologies (i.e. those delivered via digital means, such as computers and smart phones) to support or deliver health interventions. E-health interventions can take a variety of forms, from reasonably simple, primarily text-based programs (such as websites offering information) to multimedia and interactive programs that can incorporate emails or text messages, all the way up to sophisticated applications such as virtual reality systems [10]. The worldwide impact of the coronavirus disease-2019 (COVID-19) pandemic can be seen in healthcare delivery [11]. The pandemic has sped up the transition from conventional care to e-health [12]. During the epidemic, traditional physical consultations had to be minimized [13], and e-health has been intensively used to reduce the risk of cross-contamination caused by close contact [14].
The field of e‐health is a relatively new one [10], but the worldwide spread of COVID-19 unexpectedly stimulated the development of e-health [15]. It is therefore important to understand the effectiveness of e‐health family interventions, especially for parents of children aged 0–6 years with autism. The purpose of this review is to determine the current status and effectiveness of family-based interventions for parents of children aged 0–6 years with ASD in an e-health context.
METHODS
This scoping review was based on the paradigm developed by Arksey and O’Malley [16]. We adhered to the rules and guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMAScR) [17]. The PRISMA-ScR checklist was provided in the supplementary material (Supplementary Table 1). The protocol was registered in the Open Science Framework (https://osf.io/n8esh).
Search strategy
A systematic electronic search for articles was conducted on three databases (PubMed, Web of Science, and China National Knowledge Infrastructure [CNKI]) in June 2022. Search strategies were developed according to the principal concepts of the topic. Initial literature research based on different databases was conducted to create a list of alternative terms related to the concepts, including subject terms and free-text terms. Search strategies were designed separately for each data source and modified through team discussion. The titles and abstracts were searched using both subjective and free-text terms. Search terms within a concept were joined with “OR”. There were no year limits in the search strategy. The results of these searches were imported into EndNote 20 (Clarivate Analytics, Philadelphia, PA, USA), and duplicates were removed. The search strategies were reviewed by a supervisor. The complete search strategy can be found in the Supplementary Table 2.
Inclusion criteria
We established the following inclusion criteria: 1) intervention targeting parents of autistic children aged 0–6 years, 2) articles in English or Chinese, 3) abstract and full-text articles available, and 4) programs designed for family intervention for children with autism. It is worth noting that we excluded all studies that were not randomized controlled trials.
Study selection
We imported all article titles and abstracts from each database into EndNote 20. Once duplicates were removed, we screened the remaining studies in two stages: by title and abstract, and by full text. We used Rayyan (http://rayyan.qcri.org), a freely available web tool, to conduct the review. Uncertainties were resolved by discussion and consensus among the three researchers.
Data abstraction and charting
Two reviewers (WX and JZ) reviewed the titles and abstracts of studies identified by the search strategy and full texts obtained from the studies potentially meeting the inclusion criteria. The two reviewers resolved uncertainty or disagreement through discussion or, if necessary, by referral to a third researcher (CS). During the full-text review process, the following information was recorded in the data extraction table: year of publication, country, target population, age of children, sample capacity, form of intervention, duration of intervention, and so on. All the relevant data and information were charted.
Data analysis and presentation
The data were analyzed based on the themes associated with research articles using simple descriptive studies. All findings were presented with regard to the research objectives of the study. Finally, the content extracted from each study was summarized into four themes: types of intervention, duration of intervention, clinical aspects of e-health interventions, and effectiveness of the intervention.
RESULTS
Literature search
The database search produced 3,672 results, including 1,084 in PubMed, 2,078 in Web of Science, and 510 in CNKI. We reviewed 2,791 articles by title and abstract after removing duplicates, leaving 212 for full-text screening; 30 of these 212 publications matched the requirements for inclusion and were therefore included in this scoping review (Figure 1).
Characteristics of articles
Table 1 summarizes the characteristics of the selected studies. The 30 articles selected were published between 2012 and 2022 (Figure 2). We observed that the number of papers sharply increased in 2020: 12 of the 30 studies (40.0%) were published before 2020, and 18 studies (60.0%) were published in 2020, 2021, and 2022.
Figure 3 shows the region of publication of the included studies, which were published in different parts of the world. In North America, 16 studies (53.3%) were conducted in the United States. Six studies (20.0%) were conducted in Europe, in the Netherlands, France, Spain, Italy, and the United Kingdom. In Oceania, three studies (10.0%) were concluded in Australia. In South America, three studies (10.0%) were conducted in Brazil. In Asia, two studies (6.7%) were conducted, in South Korea and in Saudi Arabia. The majority (27/30, 90.0%) of the publications featured research that was primarily done in high-income countries, and 10.0% (3/30) of the papers concentrated on non-high-income nations (all from Brazil).
We conducted the analysis based on four themes derived from the primary results and objectives of each study. The four major themes were: 1) type of interventions, 2) duration of the intervention, 3) clinical aspects of e-health interventions, and 4) evidence for the effectiveness of the intervention.
Theme 1: type of interventions (n=30)
In terms of interventions, articles included video conferencing, online websites, video feedback, e-Learning programs, video modeling, Apps, web-based tutorials, and online platforms. Video conferencing was the most commonly used ehealth technology, used in 26.7% (8/30) of the interventions. The objectives are usually achieved through dedicated remote training with the support of educational videos, web-based programs, and weekly video conferencing coaching sessions with an operator [18]. An online website was used in 13.3% (4/30) of the interventions. An online website named ImPACT Online is an interactive website that teaches parents to promote their child’s social communication within the context of play and daily routines [19]. Video feedback was used in 10.0% (3/30) of the interventions. It provides the parent with an opportunity to reflect on his or her interactions with the child and the responses of the child to the interaction, with an emphasis on positive, successful interaction sequences. The intervener videotapes actual parent–child interactions at home, and in a following session watches and discusses with the parent carefully selected video-recorded episodes of parent–child interactions [20]. Other e-health interventions that were used less frequently were e-Learning programs, video modeling, Apps, web-based tutorials, and online platforms. The e-Learning program is a self-paced, interactive, web-based training system consisting of visual notes, vocal instruction, and video clips demonstrating implementation of procedures [21]. Video modeling is a mode of teaching that uses video recording to provide a visual model of the target behavior or skill [22]. An application named WhatsApp, which is a free mobile messaging application in which people can exchange private or group messages as well as visual and audio media, was used for one intervention [23]. One web-based tutorial was developed using adult learning principles designed to foster engagement, participation, and interest. The tutorial is highly interactive, making full use of the technology and principles of instructional design to enhance the learning experience [24]. Notably, eight of the interventions combined the use of two e-health technologies.
Theme 2: duration of interventions (n=30)
The total time for each intervention was between 6 hours and 12 months in all trials employing e-health interventions. Total intervention months were as follows: less than 2 months (5 articles), 2 to 5 months (12 articles), 6 to 9 months (6 articles), 1 article for more than 9 months, and the other 6 articles did not state the duration. As seen in Figure 4, the duration of a single session was different for each intervention. The most common intervention time for a single session per intervention is more than 1 hour. The shortest intervention time was 30 minutes while the longest was 2 hours. Ten studies did not describe the duration of a single session.
Theme 3: clinical aspects of e-health interventions (n=30)
These studies looked at a range of clinical aspects in children with ASD and their parents. Of the 30 articles, 27 interventions targeted only parents of children with ASD and three involved both children and parents. Of the 30 studies that made up this part, 8 findings focused on clinical aspects in ASD children, 6 findings focused on clinical aspects in their parents, 12 findings included clinical aspects in both parents and children, and the remaining studies did not show clinical results. The most studied clinical aspect concentrated in parents of ASD children was stress (n=5) and in ASD children was social communication (n=17).
Theme 4: evidence of effectiveness (n=28)
Based on the results of each trial, the effectiveness of the intervention was evaluated and categorized as either positive, negative, or mixed. The research findings were rated favorable or positive if they had a positive impact or led to advancements. Negative results, on the other hand, were labeled as such when they represented a subpar result or no change. Studies that produced both positive and negative results were referred to as having mixed findings. Efficacy was categorized based on the type of intervention.
Positive findings
Positive results were produced from 23 of the 28 studies, which demonstrated that e-health interventions are effective. This includes seven studies of video conferencing, three studies of online websites, two each for e-Learning program research, video feedback, and video modeling, one study involving an App and web-based tutorial, and five studies combining two types of intervention. These studies not only found improvements in behavior, communication, social competence, motor skills, and language among children with ASD, but also demonstrated improved parenting efficacy, reduced parental stress, and intrusiveness, etc.
Negative findings
Negative outcomes were reported in only one study, conducted using an online website [25]. The study found that online intervention did not improve sleep in parents of children with ASD.
Mixed findings
Four studies produced mixed findings, including video feedback, online website, video conferencing, and video modeling [20,26-28]. The results showed positive effects in reducing parental intrusion, enhancing self-efficacy, improving dyadic social communication, and so on. However, changes in other aspects of parent–child interaction, children’s play behavior, and children’s developmental scores failed to achieve significance.
DISCUSSION
This scoping review aimed to provide a general overview of the use of e-health as an ASD intervention, especially focused on families of children aged 0–6 years with ASD. Most of the included articles were from high-income countries. More than half of the articles reported positive findings in a variety of areas spanning all forms of e-health intervention. For children with autism, it can improve their social communication, abnormal behaviors, motor skills, language ability, cognition, eating behaviors, and sleep duration. For parents of children with ASD, it can improve their parenting effectiveness, intervention fidelity, self-efficacy, and positive perception of their child and reduce stress, depression, and intrusiveness. This suggests that e-health family interventions based on children with autism aged 0–6 years have a beneficial effect on both children with ASD and their parents.
Regarding the study characteristics, we noticed that the number of published papers has increased since 2020. This may be because more attention to e-health might have resulted from the response to the COVID-19 pandemic. It was evident that the eagerness of healthcare providers and expert researchers to share their opinions and research findings on the application and future potential of telehealth has increased. The increase in the number of e-health interventions published during the pandemic indicates the increasing recognition and use of this intervention, due not only to its flexibility and convenience, but also to its innovative and transformative role in healthcare [29,30]. In addition, the increase in the number of articles published may also be partially due to researchers working from home in the long term, caused by pandemic-related lockdowns.
Our analysis of the first authors’ affiliations and the study’s geographic focus showed that the vast majority of the publications originated from high-income countries, mainly in the Americas and Europe. This review identified a gap in such technology support for parents in lower- and middle-income countries. The highest number of publications was from the United States, which is commensurate with the recent rapid surge in e-health use seen in that country. This can be attributed to the flexibility provided by the Health Insurance Portability and Accountability Act of 1996 and the willingness of insurance companies to reimburse for the services provided via e-health [31]. E-health offers unprecedented opportunities for health interventions. However, the transition to e-health in some low- and middle-income countries faces several challenges: high adult illiteracy rates, low enrollment in primary, secondary, and higher education institutions, lack of information and communications technology (ICT) literacy, low per capita income, lack of ICT infrastructure, and limited Internet connectivity [32]. E-health is a new form of healthcare intervention that offers a low-cost, high-return alternative to traditional healthcare. Take China as an example: there are regional and rural-urban disparities in access to services and resource allocation in China, access to e-health intervention programs is often a challenge for families living in rural or remote areas, with low socioeconomic status, or experiencing other life hardships [33]. Only big cities such as provincial capitals allow families with ASD to receive an intervention, which will generate many additional costs, such as transportation, accommodation, and lost work. Future e-health research should take into account that the use of e-health in low- and middle-income countries appears to be influenced by the accessibility and affordability of technology, based on each country’s specific socioeconomic circumstances [34].
Among the types of e-health family interventions, video conferencing is the most common form. These findings demonstrate that videoconference-delivered coaching is feasible and acceptable to families, in line with shifts in recent years to this mode of intervention delivery [35]. Video conferencing provided patients with the opportunity to communicate face-to-face anytime, anywhere, effectively removing barriers in terms of time and place. It should be noted that video conferencing as a form of intervention also presented some challenges and limitations. For example, the trust relationship and communication between family members and healthcare workers may take time to establish and optimize [36]. In addition, the technical equipment and network conditions for video conferencing also have certain requirements, which may vary for families in different regions with different economic levels. Although video conferencing interventions were the most frequently used in the included articles, it is difficult to conclude which type of intervention provides the best response among the wide variety of e-health interventions. Therefore, more research is needed to answer this question.
As different studies implemented different methodologies and parameters, the effective duration might differ. A study of a web-based tutorial intervention with a total intervention time of just 6 hours showed improvements in the use of evidence-based strategies, parenting effectiveness, and children’s exhibited behaviors [24]. Another study applied both an online website and a video conferencing intervention with a total intervention duration of 6 months, but child development scores did not differ significantly between control and experimental groups [26]. Best practice recommends at least 25 hours per week of comprehensive interventions for children with ASD [37]. Additional studies have shown that greater intervention intensity (hours and duration in months) is associated with greater child gains [38].
On the clinical aspect, social communication is the most commonly studied in children with ASD. Social communication characteristics discussed in these studies include receptive communication, expressive communication, social capacity, imitation, and cognition. In e-health intervention studies targeting the clinical manifestations of ASD parents, the clinical manifestations of stress are most commonly involved, and previous research has also shown that the severity of stress in parents of autistic children is higher than that of parents of non-autistic children [39]. The studies included in this review demonstrate that electronic interventions can be effective in relieving stressful situations for parents [19,23,40,41]. A study of a parent intervention program called COMPASS for Hope explored the effects on child problem behavior, parent competency, parent stress, group alliance and parent satisfaction variables by using the Modified Checklist for Autism in Toddlers, Parental Stress Index—Fourth Edition Short Form, Vineland Adaptive Behavior Scale, Second Edition, and other scales [41].
E-health represents an alternative for those who have difficulties accessing in-person interventions or when in-person visits are not possible (e.g., the situation during the COVID-19 pandemic) [42]. E-health intervention may be an effective strategy for ASD families, as growing evidence indicates a favorable outcome for parents and for children with ASD. In a randomized trial of an electronic program, all participants who provided feedback were generally satisfied with the program and reported that the training was a helpful tool which provided an overview of all major components of applied behavioral analysis therapy (ABA). Many also reported that they had a better understanding and appreciation of their child’s ABA treatment programs after participating in e-Learning [21]. However, a REDCap-based model for online interventional research showed a negative result, and the researchers did not find that access to multimedia materials improved sleep [25]. This may be accounted for by a variety of factors. First, the sample size was relatively small; second, the study sample was heterogeneous; finally, a significant percentage of parents did not choose to view the online material. In addition, the sustainability of effects is also mixed and cannot be ascertained, as most studies have short follow-up times.
Strengths, limitations and future direction
The strength of this review was in its comprehensive search strategy, intended to find all published studies. Furthermore, unlike other scoping reviews, all of the articles included here were randomized controlled trials. The scoping review was conducted according to the suggested methodology, however we acknowledge that our study has some limitations. Our search was limited to three databases and excluded grey literature and preprints, which may have affected the comprehensiveness of our findings. In addition, some research on this topic might not be published owing to null findings. This review only included papers that were published in English or Chinese; other languages were not included, which may have led to the exclusion of some studies conducted in other parts of the world. This is a nascent field of research and more large-size randomized controlled studies are needed in the future.
CONCLUSION
A variety of e-health family interventions have the potential to help autistic children aged 0–6 years and their parents in various ways. For children with ASD, e-health interventions can improve their core symptoms and accompanying symptoms; for parents of children with ASD, it can improve their emotional problems. In the future, more studies are needed to clarify the effects of e-health interventions.
