The Need for Technology-Aided Instruction and Intervention Policy for Autistic Youth

Abstract

This paper examines current technology-aided instruction and intervention (TAII) available for autistic transition-age youth (TAY) and existing policies that may support or hinder the delivery of these interventions. Specifically, we focus on policies that might influence the delivery of TAII to autistic TAY. After a careful review of the literature, we observed that postsecondary policy guiding the delivery of TAII designed to support autistic TAY is lacking. TAII have demonstrated effectiveness, usability, sustainability, and cost-effectiveness, particularly with this population. We suggest possibilities for future policies to support the development, implementation, and evaluation of TAII for autistic TAY.

According to the latest prevalence and population estimate, approximately 80,000 autistic¹ students exit secondary education in the United States (U.S.) each year (Maenner et al., 2020; U.S. Census Bureau, 2020). It is well known that autistic transition-age youth (TAY; commonly defined as 16–26 year olds) experience substantial challenges upon aging out of (or transitioning out of) secondary education, which typically occurs between 18–21 years of age in the United States. At this time of transition, autistic TAY experience a “service cliff” (Roux et al., 2015) involving service disruption, financial burden, fragmented and underfunded services, and a lack of postsecondary education and employment preparedness and opportunities (Friedman et al., 2013). Given the term ‘transition’ covers several years, it is helpful to think of this age group in terms of pre-transition (16–17 years), transition (18–21 years), and post-transition (22–26 years). This paper will focus on the latter two groups, as the pre-transition group is somewhat covered by existing policies. Notably, some members of the 18–21 age group are covered by existing policy if they remain in special education past the age of 18 years. For the purposes of this discussion, “policy” can be defined as any federal, state, local, or organizational law, regulation, or procedure. “Intervention policy” refers to policy focused on access to interventions.

Recently, there has been a call for more research on transition outcomes among autistic TAY (U.S. Department of Education, 2018). While autistic youth (3–21 years of age) are protected by policies such as the Individuals with Disabilities Education Act (IDEA, 2004) and the Every Student Succeeds Act (2015), there is a lack of well-defined policy and legislation to support autistic TAY as they transition to adulthood (18–26 years of age). For these reasons, this paper will focus primarily on intervention policy for this autistic TAY population. Specifically, this discussion will focus on the use of technology to support this population.

Despite the benefits of interventional technology, which have demonstrated efficacy for supporting autistic individuals, existing policy is failing to keep up with its availability. For example, technology received only 13% of all autism intervention and treatment funding in 2016 (IACC, 2019). Given the widespread availability and convenience of technology as well as its critical role in intervention during the COVID-19 pandemic, we believe interventional technologies deserve greater attention, funding, and dissemination. Moreover, there are several gaps in current policy, at the national, state, local, and organizational levels, which need filled to ensure choice and effective implementation of these interventions for autistic TAY.

What is Technology-Aided Instruction and Intervention?

Evidence-based practice (EBP) is a term which originated in the medical literature and quickly infiltrated other fields including education and the social sciences (Wong et al., 2015; Buysse & Wesley, 2006; Hansen, 2010). EBP involves using scientific research-based approaches to make decisions regarding treatment interventions (Buysse & Wesley, 2006), which have demonstrated efficacy.² In order to meet criteria for an autism EBP, a practice has to contain:

(a) two high quality group design studies conducted by two different research groups, (b) five high quality single case design studies conducted by three different research groups and involving a total of 20 participants across studies, or (c) a combination of one high quality group design study and three high quality single case design studies with the combination being conducted by two independent research groups. Independence of research groups was defined as the research being located in different settings and the key constituent members of the authorship of published articles being different from other research groups (Hume et al., 2021, pp. 4019).

The National Clearinghouse on Autism Evidence and Practice (NCAEP) has identified 28 evidence-based practices (EBPs) for autism, including technology-aided instruction and intervention (TAII; Hume et al., 2021; Steinbrenner et al., 2020). According to NCAEP, TAII is “instruction or intervention in which technology is the central feature and the technology is specifically designed or employed to support the learning or performance of a behavior or skill for the learner” (p. 29; Steinbrenner et al., 2020). Despite NCAEP recently listing TAII as its own EBP, technology can arguably be incorporated into most of the other 27 EBPs. To this point, the Autism Focused Intervention Resources and Modules (AFIRM; a resource of the National Professional Development Center [NPDC] on Autism) has a TAII planning worksheet to determine if TAII is appropriate. Such a worksheet can be used by teachers to assess whether TAII is feasible for a particular student and, if so, the level of support that will be needed.

According to Hedges and the AFIRM Team (2017), TAII can be used by a variety of professionals to address academic and social skills, joint attention, behavior, and communication. Additionally, most TAII can be easily altered or updated, accessed in a variety of settings with limited equipment, are attractive to autistic individuals, and do not generally rely on professional service providers to function, making them more convenient and affordable (Moore et al., 2005; Parsons & Mitchell, 2002). Because of its novelty, malleability, convenience, and self-delivery capability, TAII is one solution to the dilemma of autism intervention selection.

Technology is pervasive in modern-day society; aside from the targeted skills an intervention aims to benefit, individuals also gain technology experience and training simply by engaging with the technology. To this end, TAII has not only been found to be effective (Grynszpan et al., 2014), but individuals are also able to gain marketable job skills through the use and practice of technology. For these reasons, the prevalence and popularity of TAII has increased over the past decade, as noted by its introduction into the NCAEP evidence-based practices report in 2015 (Wong et al., 2015).

Moreover, TAII is a useful tool for autistic individuals because it eliminates the social demands they would experience during a face-to-face interaction (Grynszpan et al., 2014). This self-delivery aspect also minimizes reliance upon service providers and eliminates the barriers that are attached to service provider-dependent interventions (DiGennaro Reed et al., 2011). Additionally, individuals in rural areas have a particularly difficult time locating or gaining access to services (Ashburner et al., 2016). Thus, TAII could ameliorate this problem by providing remote access. In general, transition-age is a time when independence and autonomy are increasing and reliance on teachers, therapists, and parents is decreasing. With technological modalities, autistic individuals can often use TAII without the pressure of having a live person present. Moreover, autistic TAY find TAII to be highly acceptable (omitted citation; Spencer et al., 2019). Thus, TAII can help close the gap in services for autistic individuals in rural areas by providing more cost-effective, convenient, reliable, acceptable treatment options (omitted citation; Ashburner et al., 2016). Other benefits of TAII are the visual cues commonly used in technology and reduced distractions from unnecessary sensory stimuli, both which can be helpful for autistic individuals (Grynszpan et al., 2014; Bozgeyikli et al., 2017; Quill, 1997).

However useful, there are some drawbacks to using technology, which should be considered within the context of policy. For example, technology can be more expensive than non-technology options; however, research is still needed to evaluate the cost effectiveness and budget impact of technology (DiGennaro Reed et al., 2011). There can also be a learning curve, both for the user and the interventionist, resulting in the possible need for more resources to train teachers and support students to engage with technology. Further, users can have sensory needs which might prohibit the use of certain technologies (e.g., virtual reality headsets; Newbutt et al., 2016). While this list of potential drawbacks is not exhaustive, we believe it provides some insight into the limitations of technology in general.

Overall, autistic TAY can greatly benefit from the use of technology as a form of intervention (Odom et al., 2015). More specifically, some technologies enable autistic TAY to receive treatment without being wholly dependent upon an interventionist and provides structure for independent achievement. As autistic TAY transition into adulthood, the ability to advocate for themselves and manage their own needs evolves into a vital set of skills. Thus, technology can encourage and assist with this transition to adulthood.

Review of Technology-Aided Instruction and Interventions

Technology can be divided into two groups: low-tech, which refers to non-electronic devices, and high-tech, which refers to an electronic item, application, or network (CSESA Technology Group, 2013). For the purposes of this paper, we will focus on high-tech interventions, including virtual environments, games, and robots, as well as providing a brief overview of mobile devices and applications. Assistive technology is a broader concept and is already covered extensively in the literature and so it will not be explicitly referenced here, although some (or all) of the TAII we discuss could be considered assistive technology. While this list provides an extensive summary of interventions and technologies, it is in no way exhaustive. Additionally, some of the mentioned TAII are not yet considered evidence-based by NCAEP standards, but can be more accurately referred to as promising practices.

Virtual Environments

Virtual environment (VE) is an umbrella term for multiple types of virtual technology, including virtual reality (VR), collaborative virtual environments (CVE), and virtual conversation partners. According to Miller and Bugnariu (2016), VEs may be the ideal method for carrying out social skills training for autism, as the VEs are able to closely mimic real-world environments, thereby strengthening the likelihood that skills will transfer. VEs have proven to be particularly effective in autistic individuals because of the somewhat predictable, less threatening environment, as well as their ability to be modified and adapted for individualized use depending on the user’s needs and abilities (Parsons et al., 2000).

Virtual reality (VR) interventions for the autism community have caught on quickly due to their appeal with autistic individuals (Burke et al., 2018; Burke et al., 2021; Kandalaft et al., 2013; Kinsella et al., 2017; Parsons & Cobb, 2011; Parsons & Mitchell, 2002; omitted citations; Strickland et al., 2007; Strickland et al., 2013; Tartaro & Cassell, 2007; Wang & Reid, 2011). For some VR platforms, the virtual environment can be accessed through a head-mounted device (e.g., Oculus Quest) or through a computer-screen interface. While head-mounted devices arguably provide more of an immersive virtual experience, they are more expensive, have limited scalability, and autistic individuals may have a difficult time adjusting to the weight and feel of the headset, as they can be somewhat cumbersome and uncomfortable (Newbutt et al., 2016). Meanwhile, the computer-screen interfaces are more prevalent, affordable, and accessible, and have the capacity to provide a reasonably similar realistic environment and generalizable learning experience for users (Strickland et al., 2007). There are many possibilities and features to be used within VR which are discussed below.

One form of VR is the collaborative virtual environment (CVE), which is an internet-based virtual environment where multiple users can interact synchronously using avatars on their computer screens (Moore et al., 2005). Many online video games use CVEs. The benefits of a CVE include real-time social interaction and responses (i.e., users can respond to each other’s statements in a very specific, detailed way; Bishop, 2003; Parsons & Mitchell, 2002). Some of the limitations of CVE include the requirement of more than one user interacting at a time; the technology is wasted if only one participant joins. For this reason, some researchers use clinical “coaches” or guides within the CVE to coax users and guide them through the environment (Burke et al., 2018; Didehbani et al., 2016). The obvious limitation with this approach is the time required by a clinician or researcher to facilitate the interaction and provide feedback.

A common component of virtual technologies is the virtual conversation partner (Trepagnier et al., 2011). This feature consists of an automated virtual character that provides relevant, naturalistic feedback to autistic users to teach conversational skills through self-directed, repetitive practice. Some studies that used this technology include a speech recognition feature to enhance the realistic feel of the environment (omitted citation). [omitted citation] and colleagues (omitted citations) used a virtual conversation partner to engage autistic TAY in virtual job interviews. These studies also used a job coach feature, which was a separate virtual character who provided real-time feedback via non-verbal cues throughout the social interaction.

Games

TAII frequently utilize gaming components, such as tokens, scoring, leveling up, and storylines commonly seen in video games and computer games. Autistic and non-autistic individuals do not always have an intrinsic motivation to engage in social situations with one another (Chevallier et al., 2012; Morrison et al., 2020), so these concrete, extrinsically motivating gaming features can encourage them to complete interventions successfully. In contrast to “entertainment games”, the educational literature describes “serious game design” as a method to designing intentional games for the learning of a particular skill or set of skills (Whyte et al., 2015). These types of games are used in the process of designing game-based interventions with the intention of influencing real life outcomes. These features can also crossover into virtual environments (see above).

One study focused on a computerized game to teach face processing to autistic children (Tanaka et al., 2010). The Let’s Face It! game used gaming features such as increasing difficulty, original music, and attractive graphics, and resulted in autistic participants being able to better recognize eye and mouth features (Tanaka et al., 2010). Unfortunately, some of the autism-focused games marketed to families and schools have little-to-no evidence to support their efficacy, effectiveness, and implementation feasibility. Thus, autistic individuals, their families, and providers need better guidance on how to differentiate between the evidence-based and non-evidence-based games being marketed to them.

Robots

Also appealing to autistic individuals is the use of robots for purposes of intervention. Robots are attractive as an autism intervention because of their ability to exhibit human-like features and behaviors, which can translate into skill development in joint attention, motivation, behavior, and social skills (Bekele et al., 2013; Feil-Seifer & Mataric, 2009; Goldsmith & LeBlanc, 2004; Scassellati et al., 2012; Werry et al., 2001). Several studies have focused their efforts on the effectiveness of robot-use with the autistic population (Martinez-Martin et al., 2020; Melo et al., 2019). Robots have even been used in a mock job interview setting with autistic young adults, resulting in increased self-confidence and lower cortisol levels (Kumazaki et al., 2017). Despite these promising results, there were some limitations to this study including small sample size and a narrow range of cognitive ability within the sample.

One of the benefits of robotic intervention is the capability of robots to collect and analyze data during interaction for future use in individualizing interactions (Bekele et al., 2013). Some of the criticisms of robot-assisted technology include high cost and limited scalability (Scassellati et al., 2012). Additionally, more longitudinal research is needed to determine whether the successes of robot-assisted interventions are generalizable to the real-world and hold over time and not simply a result of novelty (Bekele et al., 2013; Robins et al., 2004).

Mobile Devices and Telehealth

Some interventions can be used with a mobile device, such as a tablet or smart phone. These can include social stories (Gray & Garand, 1993; Karkhaneh et al., 2010; Vandermeer et al., 2015), video modeling (Bellini & Akullian, 2007; Charlop et al., 2010), and many applications with game-like features for autistic TAY. Most of these revolve around teaching social skills or executive functioning skills such as organizing and scheduling.

Telehealth is another form of technology-based intervention that can be effective with autistic individuals (Baharav & Reiser, 2010). Telehealth can include remote assessment, intervention, and consultation between a clinician and client (Baharav & Reiser, 2010). These interventions are convenient due to the abundance of mobile devices available today and less stigmatizing for autistic adolescents and adults (Bowers, 2011). Telehealth has been particularly popular and critical during the COVID-19 pandemic and could continue to increase in use.

Review of Autism Intervention Policy

In an effort to meet the demands of an autistic TAY population that has grown from approximately 235,000 to more than 700,000 over the past 20 years³ (U.S. Census Bureau, 2020; CDC, 2020; U.S. Census Bureau, 2010), there has been a recent push from stakeholders for the development of innovative, effective interventions that can be feasibly delivered at scale with high fidelity and sustained within secondary education transition services (U.S. Department of Education, 2018). One result of the push by stakeholders is increased pressure on schools, government agencies, and policymakers to ensure interventions are evidence-based, cost-effective, scalable, and have realistic implementation strategies. The process of intervention selection and implementation is analogous to the project management triple constraint of balancing time, cost, and quality (Weaver, 2007). For interventions focused on supporting autistic TAY, the triple constraint includes type of setting (time/place), available funding (cost), and implementation strategy (quality); all which are affected by, and drive, policy decisions.

Setting

Secondary education is a mandated setting for interventions supporting autistic TAY, given that autism is covered as a qualified disability in the U.S. under IDEA Part B for children ages 3 through 21 years (IDEA, 2004) and under Section 504 of the ADA (1990). Specifically, services to support the transition into adulthood are documented in an individualized education program (IEP), which is overseen by an IEP team consisting of parents/guardians, students with a disability, general and special education teachers, local education agency representatives, and other service professionals (e.g., transition coordinator, social worker).

For autistic TAY receiving special education services, IDEA (2004) mandates that transition planning must begin before the individual’s sixteenth birthday. Toward this effort, school districts coordinate a transition team (including the IEP team and vocational rehabilitation specialists) which integrates a formal transition plan into the student’s IEP. Moreover, the transition team is responsible for making sure the transition plan will facilitate the student’s transition into postsecondary education, employment, or other structured activities after they graduate or age out of special education services.

Many government-funded services, such as those covered under IDEA, decrease or end right at the time autistic TAY are eligible to seek employment or join postsecondary education programs. Thus, many autistic TAY are left with fragmented and underfunded services at a time when youth need is high. Transition programs are a vital piece of the service puzzle to ensure autistic TAY are not left without services when the autistic TAY leaves secondary education.

The federal Every Student Succeeds Act (ESSA, 2015) promotes the use of evidence-based practice (EBP) in schools. This legislation applies to all school-aged children, including general and special education students. Thus, schools are an ideal setting for implementing EBPs to support autistic TAY. However, there are several barriers to the implementation of EBPs in schools (e.g., lack of funds, lack of training, understaffing; Bellini et al., 2007). For autistic TAY who plan to transition directly into the workforce, Pre-Employment Transition Services (Pre-ETS) are particularly important before they age out of the services provided to them under IDEA. Pre-ETS are mandated by the Workforce Innovation and Opportunity Act (WIOA, 2014) and require state vocational rehabilitation agencies to offer services such as job exploration counseling, work-based learning experiences, counseling on postsecondary education planning, workplace readiness training, and instruction in self-advocacy to students who are eligible or potentially eligible for vocational rehabilitation services.

Funding

In 2016, federal government and private organization funding for autism research totaled over $364 million; however, only 2% of that total was spent on lifespan issues, including transition to adulthood (IACC, 2019). Current governmental funding streams for autism include the Department of Education, Health Resources and Services Administration, Vocational Rehabilitation Services, Centers for Medicare & Medicaid Services, Department of Labor, Workforce Investment Act waivers, and Community Mental Health Authorities, among other public and private sources. Many programs and individuals benefit from some combination of braided funding from multiple agencies (federal, state, and local) to meet their complex needs (Nichols et al., 2011). Despite these funding streams that can facilitate access to interventions, individuals, families, and agencies still face large funding gaps, which results in individuals and families paying out-of-pocket, battling with insurance companies, or being unable to access the intervention altogether (Davidoff, 2004; Kuhlthau et al., 2005).

A critical piece of the policy dialogue is insurance coverage for autistic individuals. Lack of insurance coverage for many interventions significantly limits the lives of autistic individuals and has resulted in a national dialogue over lack of choice in treatment (Kogan et al., 2008; Schott et al., 2020). Over the past two decades (2001–2019), all 50 U.S. states have taken part in some level of autism insurance reform. However, when reviewed closely, this reform largely resulted in the coverage of only one type of intervention, Applied Behavior Analysis (ABA), and only for state-regulated health plans (Autism Speaks, 2020). Many other evidence-based interventions (e.g., social skills training, video modeling, and technology-aided instruction and intervention) have been left out of insurance reform (Wong et al., 2015). Given that it took 20 years to obtain coverage for ABA, it could take decades to organize another social movement of that magnitude. Policymakers must be made aware of the impact the lack of insurance coverage for autism services has on autistic individuals and their families.

It is important to note that the cost of individual interventions could potentially be cost-prohibitive for some. Although research in this area is lacking (Eisman et al., 2021), there are some findings for non-technology interventions such as Positive Behavior Intervention Support (PBIS) and Applied Behavior Analysis (ABA). PBIS can cost upwards of $25,000 per school annually for meetings and training alone (Bradshaw et al., 2020), while ABA can cost as much as $40,000 per student per year (Cakir et al., 2020; Chasson et al., 2007). However, more research is needed on individual technology interventions.

Implementation Strategy (Type, Quality, and Dosage)

According to the Autism Focused Intervention Resources and Modules (AFIRM; an extension of the NPDC on Autism), the process of selecting an EBP requires four steps: 1) identifying a behavior or skill; 2) defining the extent of the behavior (collecting baseline data); 3) establishing an observable and measurable goal or outcome; and 4) choosing an EBP (NPDC, n.d.). This process was established to serve as a guide for providers working with autistic individuals. After following this process, providers then decide which intervention is realistic for them to implement with regard to the setting and available funding.

That said, once an EBP has been chosen, the intervention team can proceed with choosing a strategy to implement the intervention. The appropriate dosage or frequency, of an intervention varies significantly between individuals and intervention type. In a meta-analysis of the social skills training literature, Gresham and colleagues (2001) found that 30 hours of intervention exposure spread over 10–12 weeks was not enough to effect change in social skills. Other interventions, such as behavior modification treatments, suggest upwards of 40 hours per week to facilitate behavioral change (Lovaas, 1987; Reichow, 2012). As an alternative, other interventions required approximately 3 hours of interactive training to facilitate a measurable change in skill (omitted citation). Due to the heterogeneous nature of autism, the translation and implementation of EBPs by service providers should be heavily guided by the literature to ensure that EBPs are carried out as designed (Palinkas & Soydan, 2012; Proctor et al., 2009).

In addition to setting, funding, and implementation strategy, autistic individuals, families, and service providers must decide whether to implement the intervention using a technology-based or a non-technology-based approach (Bellini et al., 2007). Decisions should be based on individual student preferences and abilities, as well as the knowledge of service providers, and to the extent policy allows. While there are many effective, widely disseminated non-technology-based treatments, this discussion focused on the increasingly effective and accessible TAII.

Implications and Policy Recommendations

As with most challenging and complex issues, there are multiple approaches to improving policy, each with its own set of implications. A small sample of policy recommendations will be presented here (see Table 1 for a summary of these recommendations).

Table 1.

Technology-Aided Instruction and Intervention for Autism Policy Recommendations

1. Separate the TAII EBP into multiple types of intervention, such as virtual environments, games, robots, and mobile applications.

2. State and local policymakers should ensure service providers have access to the latest technology-based EBP research.

3. Policies centered around advancing autism insurance reform should include more than one EBP.

4. Technology-based interventions should be delivered to youth with ASD in school settings or transition programs.

5. WIOA waivers and vocational rehabilitation funding should be expanded to include more technology-based interventions.

6. Braided funding from multiple agencies should be used for technology-based interventions.

Virtual environments, games, robots, mobile devices, and applications can all be considered TAII under the current definition. However, if policy is to advance the accessibility of autism interventions and reflect the growing research base, NCAEP must separate the various types of TAII into separate EBP categories. As technology evolves and use expands, one category does not do justice to the importance and need of technology in autism interventions. In the same way that many of the behavioral interventions stand alone as separate EBPs (Steinbrenner et al., 2020) rather than under one larger umbrella category, the various forms of TAII can be teased apart very clearly as more research is produced on these interventions. For example, virtual environments, games, robots, and mobile applications could each be classified as separate EBP categories going forward. Overall, the process of identifying technology that aligns with EBP criteria should still be left to the cyclic NCAEP reviews. Of course, individual interventions within each of these categories would still require an independent evaluation of their effectiveness in order to meet NCAEP EBP standards.

The majority of public policy surrounding autism has focused on etiology, insurance reform, and research opportunities (Baker, 2013), while details of which interventions to explore, include, or exclude have largely been left up to local school districts, vocational rehabilitation agencies, individual service providers, autistic individuals, and/or their families. Until recently, basic services such as speech and occupational therapy were not covered for autistic individuals under many insurance policies (Choi et al., 2020; Zhang & Baranek, 2016). The last few states recently underwent autism insurance reform to include ABA as an approved autism treatment (Autism Speaks, 2020). But what about the other 27 EBPs identified by NCAEP (Hume et al., 2021; Steinbrenner et al., 2020)? And where will autistic TAY receive these services once they transition out of secondary education? Policies centered around advancing autism insurance reform to include more than one EBP would allow individuals to have freedom of choice when reviewing treatment options. However important, the review and suggested reformation of specific insurance policies are beyond the scope of this paper.

Despite research suggesting that intervention delivery is more effective when implemented in a more naturalistic (i.e., non-clinical, non-laboratory) setting, families in rural communities are still largely obligated to drive their children great distances to receive treatment (Skinner & Slifkin, 2007). While some services are currently delivered in the school setting (i.e., speech, occupational, and physical therapy), there are few policies regarding the implementation of TAII for autistic TAY in schools. With overwhelming evidence of the importance of social skills to both academic and postsecondary outcomes (Nasamran et al., 2017; Parsons & Mitchell, 2002), as well as a collection of well-trained professionals in the school setting, it would make sense to deliver interventions to autistic TAY in the school setting or in transition programs. However, other settings would be needed for adults to receive these interventions (e.g., home, work, postsecondary education, vocational rehabilitation).

Government funding streams such as Medicaid’s Home-Based Community Waivers, the Rehabilitation Act’s Vocational Rehabilitation grants, and WIOA waivers can facilitate access to specific evidence-based services for autistic TAY. However, these current policies fail to include specifics related to the usage and implementation of TAII. Further, the field of TAII research for autism is growing at such a rapid rate, it would be difficult to constantly update federal policies to reflect the current best EBPs. For this reason, it is the responsibility of state and local policymakers to ensure that service providers, individuals, and families are informed of the latest research in autism EBP. To do this successfully, service providers and families need time, money, guidance, and support. Additionally, autistic individuals and their families should be able to request that their individual funding goes toward specific EBP(s).

Of particular interest to autistic TAY and stakeholders are those interventions which include some form of workforce preparedness, whether in the form of soft skills, such as social communication, or hard skills, such as technical knowledge. Many of these interventions would fit nicely into Pre-Employment Transition Services offered by state vocational rehabilitation and would flatten the “service cliff” often experienced by autistic TAY. Current state systems often require a company to register as a vendor within vocational rehabilitation services prior to wide-scale use by counselors. This process could be automated or simplified to allow counselors access to EBP, even if there is not a single commercial vendor.

One solution would utilize braided funding from multiple agencies (e.g., Department of Education, Department of Labor, Workforce Investment Boards, Rehabilitation Services Administration) to fund access to TAII. This braided funding approach is in line with current funding approaches and would reduce financial burden on individual agencies. Current funding streams must be redirected from outdated interventions to include new, effective TAII.

Conclusion

Autistic TAY are a critical population that deserves our attention in the areas of education, intervention, public policy, and employment. There continues to be an increasing number of EBPs available to this population, but public policy has not addressed the issue of accessibility, funding, or implementation of TAII specifically. Rather than lumping all TAII into one category, researchers and policy makers must give credit to the large number of effective and efficacious TAII that continue to become available to the autism community. Separating TAII such as virtual environments, games, and robots into their own categories of EBP and promising practices would better represent these interventions and allow for more public attention and funding of these options. Additionally, an increase in dissemination of information and resources surrounding TAII for autistic TAY is a critical piece of ensuring individuals have access to the interventions that most benefit them in their transition to adulthood. Finally, this paper is a call for 1) more research on evaluating the efficacy, effectiveness and implementation of individual TAII and 2) more systematic reviews of these interventions so we can more clearly understand what works, for whom, and under what conditions. In conclusion, the goal of this paper is not to analyze or critique a specific policy, but to build a dialogue around taking proactive steps to update our policy focus in the near future. Thus, we hope this discussion has generated productive thinking around TAII for autistic TAY and that others will take this information and carry the field, and policies, in a forward direction.