Augmentative and Alternative Communication, 2015; Early Online: 1–12 © 2015 International Society for Augmentative and Alternative Communication ISSN 0743-4618 print/ISSN 1477-3848 online DOI: 10.3109/07434618.2015.1047532

RESEARCH NOTE

AAC Interventions for Individuals with Autism Spectrum Disorders: State of the Science and Future Research Directions

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Jennifer B. Ganz Department of Educational Psychology, Texas A&M University, College Station, TX, USA

Abstract

Augmentative and alternative communication (AAC) provides a means of effective communication to individuals with autism spectrum disorder (ASD), many of whom are unable to use conventional speech effectively. The purposes of this article are (a) to summarize and synthesize the last few decades of research on the use of AAC with people with ASD; (b) to indicate implications of this research for stakeholders such as people with ASD, their family members, and educators with whom they work; and (c) to outline priorities for future research to improve communication and other outcomes for individuals with ASD and their loved ones. People with ASD stand to greatly benefit from AAC, particularly with current AAC technologies, as described in this article.

Keywords: Augmentative and alternative communication (AAC); Aided AAC; Assistive technology; Autism spectrum disorder; Communication

Introduction

have difficulty using and comprehending nonverbal communication (APA, 2013), including difficulty using and understanding facial expressions, tone of voice, eye contact, and body language (Kanner, 1971; Matson, Dempsey, & LoVullo, 2009; Shriberg et  al., 2001). Finally, individuals with ASD have deficits in forming and maintaining relationships compared to same-age peers (APA, 2013). These deficits include showing minimal interest in others, neglecting to maintain contact with others, having fewer friendships and less intimacy with others, and appearing to prefer being alone (Kuo et  al., 2013; Matson et  al., 2009; Rowley et al., 2012; Solomon et al., 2011). These deficits often become more apparent as children get older and social and communication expectations increase in quantity and complexity (Tantam, 2003). Although language impairment is no longer included within the core social-communication criteria for ASD, it is considered an additional potential descriptor within the ASD diagnosis (APA, 2013). The diagnosis includes a rating of severity in the social-communication domain, wherein Level 3 is considered to be the most severe, or that the person requires major supports (APA, 2013). People with ASD with this level of severity would likely be at high risk for complex communication needs and would likely benefit from AAC. Furthermore, individuals

According to the United States Centers for Disease Control and Prevention (CDC, 2014), approximately 1 in 68 children has a diagnosis of autism spectrum disorder (ASD). This represents a rapid increase in diagnoses. Similarly, increasing prevalence has been observed recently in Israel (Davidovitch, Hemo, Manning-Courtney, & Fombonne, 2013), Sweden (Nygren et al., 2012), and Taiwan (Lai, Tseng, Hou, & Guo, 2012), although not at rates as high as in the US. ASD is characterized by social-communication deficits and restricted and repetitive behaviors (American Psychiatric Association [APA], 2013). Individuals with ASD have social-communication deficits in the following three areas, all of which may impact their communication and speech skills and their responsiveness to augmentative and alternative communication (AAC) interventions. First, they experience difficulties with emotional reciprocity or understanding and inferring others’ thoughts and feelings (APA, 2013; Kuo, Orsmond, Cohn, & Coster, 2013). They may be less likely than typically developing peers to orient toward other people, resulting in less frequent and poorer quality interactions (Kuo et  al., 2013). They may infrequently take turns or share information and interests (Rowley et  al., 2012). Second, people with ASD

Correspondence: Jennifer B. Ganz, Department of Educational Psychology, 4225 TAMU, Texas A&M University, College Station, TX 77843, USA. E-mail: [email protected] (Received 1 September 2014; revised 14 March 2015; accepted 19 April 2015)

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2    J. B. Ganz with ASD and complex communication needs are more likely to have associated intellectual disabilities (Hewitt et al., 2012; Luyster, Kadlec, Carter, & Tager-Flusberg, 2008) and oral-motor difficulties (Gernsbacher, Sauer, Geye, Schweigert, & Goldsmith, 2008).This further complicates their responsiveness to AAC interventions. It is particularly critical to address these needs early because a lack of effective communication skills negatively impacts outcomes in all domains, including social-communication, academic, behavioral, and post-secondary outcomes (Branson & Demchak, 2009; Hamm & Mirenda, 2006). Overall, individuals with ASD and complex communication needs are more likely to require intensive services and supports throughout their lives, particularly if communication is not addressed prior to secondary school completion (Hewitt et al., 2012). Further, severe deficits in social interest and understanding set people with ASD apart from other people with disabilities who have complex communication needs. Many people with complex communication needs (e.g., people with cerebral palsy or Down syndrome) are interested in communicating with others and have a basic intuition regarding how communication works, although this may not be the case for individuals with both ASD and complex communication needs. AAC intervention for people with ASD is a critical area of research, particularly because the prevalence of ASD is rising and because these individuals are at high risk for complex communication needs. There are three key purposes of this article: (a) to summarize and synthesize the state of the science related to individuals with ASD and AAC; (b) to provide insights relating to the implications of this research, particularly the implications for people with ASD, their family members, and service providers; and (c) to suggest priorities for future research related to individuals with ASD and AAC, reflecting on the above-mentioned state of the science and implications for stakeholders.

Synthesis of Research on AAC and Individuals with ASD Over the last few decades, a large body of research, primarily single-case experimental design, has demonstrated the efficacy of AAC for people with ASD. Studies have been published on a variety of AAC modes, including manual sign language, exchange-based communication, and speech-generating devices. Practitioners and family members often question which modes of AAC will produce the best results, or the best means of functional communication. The sections that follow will cover the research to date on: (a) effective modes of AAC, (b) designs for AAC systems that reduce learning demands and maximize performance, (c) choice and preference in AAC interventions, (d) the impact of AAC on particular communication skills and functions, (e) generalization of AAC skills across communicative partners and contexts, and (f) unsubstantiated fad AAC

treatments. Although other topics could have been covered, due to space constraints, these were selected for review due to their prominence in the recent literature, or their importance to families and individuals with ASD and complex communication needs. Effective AAC Modes for People with ASD Research has produced more support for aided AAC than manual sign language for people with ASD, although a few studies have been conclusively deemed to demonstrate the effectiveness of manual sign language (Schlosser & Wendt, 2008a). Literature has addressed the use of sign language with people with ASD since the 1970s (Ganz & Gilliland, 2014). At best, this literature can be described as demonstrating weak or questionable effects, in some cases resulting in learned use of a small number of signs with a small number of participants (Bonvillian & Nelson, 1976; Carr, 1979; Hinerman, Jenson, Walker, & Petersen 1982; Remington & Clarke, 1983). In many reports, participants with ASD learned only a limited number of sign vocabulary words, and teaching of these few signs often required much time and effort (Carr, Binkoff, Kologinsky, & Eddy, 1978; Carr, Kologinsky, & Leff-Simon, 1987; Falcomata, Wacker, Ringdahl, Vinquist, & Dutt, 2013; Hinerman et al., 1982; Kee, Casey, Cea, Bicard, & Bicard, 2012; Remington & Clarke, 1983; Valentino & Shillingsburg, 2011). Finally, much of the literature in support of using manual sign language includes anecdotal reports, case studies (Bonvillian & Nelson, 1976; Kee et  al., 2012; Konstantareas, Hunter, & Sloman, 1982), and underpowered group designs (Watters et al., 1981). Given this body of literature, it seems apparent that unaided AAC is not the most effective and efficient means of providing functional and spontaneous communication for most people with ASD. This is not to say that sign language is never effective for individuals with ASD; however, sign language has not been highly effective for many or most individuals with ASD (Ganz & Gilliland, 2014). In studies that have evaluated preference, sign language is infrequently selected by children with ASD (e.g. van der Meer, Sutherland, O’Reilly, Lancioni, & Sigafoos, 2012). Both low-tech and high-tech aided AAC systems have been demonstrated to be effective with people with ASD. Both picture-exchange-based AAC and speechgenerating devices (SGDs) have been demonstrated, via meta-analyses and systematic reviews, to have at least moderate effects overall on outcomes for people with ASD (Flippin, Reszka, & Watson, 2010; Ganz, Earles-Vollrath, et al., 2012; Ostryn, Wolfe, & Rusch, 2008; Preston & Carter 2009). Although recent papers have investigated the use of current technologies (e.g., handheld-device and tablet-based AAC applications or apps) with people with ASD (Flores et  al., 2012; Ganz, Boles, Goodwyn, & Flores, 2014), this is an emerging area, and the efficacy of these technologies is unclear. Furthermore, and perhaps more importantly, Augmentative and Alternative Communication

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State of the Science in AAC and ASD    3 only one instructional protocol – the Picture Exchange Communication System (PECS; Frost & Bondy, 2002) – has been succinctly described and thoroughly investigated, although most of this work has focused on early phases of the protocol that target requesting skills (Ganz et al., 2012). Meta-analytic techniques have been used for preliminary investigations to determine for whom, among people with ASD, aided AAC is most effective (Ganz, 2014; Ganz, Mason, et al., 2014). In particular, people who had ASD without other co-occurring diagnoses had significantly better results with aided AAC interventions than those with ASD plus intellectual disabilities or sensory impairments (Ganz, Earles-Vollrath, et al., 2011). However, when disaggregated by disability category and mode of AAC, individuals with ASD and intellectual/ developmental disabilities had statistically significantly better results with both PECS and SGDs than individuals with ASD alone. Furthermore, people with ASD and intellectual/developmental disabilities performed statistically significantly better with SGDs than with PECS (Ganz, Mason, et al., 2014). Youngsters also had significantly better results than older people when considering AAC interventions in aggregate (Ganz, EarlesVollrath, et al., 2011). In addition, for both SGDs and PECS, preschoolers significantly outperformed all other age groups evaluated (Ganz, Mason, et al., 2014). To a degree, however, these studies should be interpreted with caution because PECS includes a distinct instructional protocol while SGDs are a mode of AAC and thus these approaches are not equivalent or directly comparable. Designs that Reduce Learning Demands and Maximize Performance Although availability of mobile technology has become ubiquitous, the focus must remain on individuals who use ASD, rather than on the technology (Light & McNaughton, 2013). Accordingly, research has begun to investigate high-tech AAC designs that best match strengths and challenges (e.g., visual, cognitive, and linguistic processing) in people with ASD and other disabilities (Light & McNaughton, 2014). This research may positively impact assessments for and design of AAC interventions (Light & McNaughton, 2013). Eye tracking technology has been successfully used to measure the receptive language understanding (e.g., matching spoken words with images) in children with ASD, which may be useful in selection of AAC vocabulary (Brady, Anderson, Hahn, Obermeier, & Kapa, 2014). Further, visual scene displays that incorporate photographs, often with familiar settings and people, have begun to be investigated for use in AAC, in contrast to typical gridbased AAC displays (Blackstone, 2005). These visual scene displays contain hotspots that embed sounds or speech into the images, with the purpose of promoting language via natural contexts (Wilkinson & Light, 2014). Previous eye-tracking research indicated that © 2015 International Society for Augmentative and Alternative Communication

young children with ASD do not look at people at rates as high as their peers (Anderson, Colombo, & Shaddy, 2006). However, recent research has suggested that incorporating human figures into visual scene displays may increase attention to the images in older children with ASD (Wilkinson & Light, 2014). This literature base, albeit preliminary, points to the need to ensure that the technology is a good fit for the individual with ASD and complex communication needs, lest the technology be abandoned (Light & McNaughton, 2013). Caution should be taken in interpreting much of the display research because, to date, much of the work has been conducted with high-functioning individuals with ASD rather than those with complex communication needs, and because the studies have been conducted in laboratory settings instead of real-world applications (Gillespie-Smith & Fletcher-Watson, 2014). Choice and Preference in AAC Interventions Over the last decade or so, researchers have investigated the preferences of people with ASD for particular modes of AAC (Ganz, 2014; van der Meer, Sigafoos, O’Reilly, & Lancioni, 2011). This work has often involved conducting preference assessments. For example, one might put two or more modes of AAC, including low-tech AAC, high-tech AAC, and images representing manual sign language, in front of an individual and ask him or her to take or point to the preferred system (Cannella-Malone, DeBar, & Sigafoos, 2009; van der Meer et  al., 2011). Preferences have been assessed both before and after the interventionists provided instruction in the use of the systems (Ganz, Hong, & Goodwyn, 2013; van der Meer et al., 2012), most often after the individual has demonstrated at least a basic ability to use the systems (Cannella-Malone et  al., 2009). To date, the participants in these studies have varied greatly in their demonstrated preferences, and it is unclear which factors are at play (Ganz, 2014). Variables such as familiarity, preference for technology, and mastery of particular modes may be involved. As a group, people with ASD do not demonstrate a strong preference between types of aided AAC. AAC Interventions to Target Communication Skills and Communicative Functions Although aided AAC systems have been deemed to be more effective in improving communication skills than other skills, they are also at least moderately effective in addressing challenging behaviors and social interactions skills, according to recent meta-analyses (Ganz, Davis, Lund, Goodwyn, & Simpson, 2012; Ganz, Earles-Vollrath, et  al., 2012). Challenging behaviors appear to be more greatly impacted by SGDs than by picture-exchange-based systems, although more studies are needed before these results can be interpreted with confidence (Ganz, Rispoli, Mason, & Hong, 2014). Unfortunately, most of the research involving AAC and people with ASD has focused on behavior regulation,

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4    J. B. Ganz or use of communication to request or protest, to the exclusion of most other communicative functions (Ganz, Earles-Vollrath, et al., 2012). Specifically, much work has been done on requesting skills and very little research has been conducted on how to best teach other types of communication skills (e.g., socially-motivated joint attention). Meta-analytic methods have been used to investigate the relationship between speech at outset of the intervention and speech outcomes as measured throughout the study. Ganz, Mason, et al. (2014) found that children who had some speech at study onset had significantly more improvement in speech than those who demonstrated no speech prior to intervention. That is, although not an explicit target of AAC and although some stakeholders fear that speech will be impeded by AAC, in fact, in some children with ASD, AAC has enhanced speech skills. Schlosser and Wendt (2008b) also suggest, via a systematic review, that AAC has no negative and at least moderate positive effects on speech in some children with ASD. Context in which AAC is Implemented Meta-analyses and single-case studies have begun to investigate the implementation of AAC across varied contexts, including types of educational settings, with varied communicative partners, and across didactic and naturalistic settings. Some of this work has pointed to AAC implementation in general education as more effective than in other settings (Ganz, Rispoli, et al., 2014); however, without additional study, it is unclear what other confounding variables, such as functioning level, may be at play. A few studies have indicated that implementation of AAC in natural contexts may be as effective with people with ASD as implementation in didactic, highly structured contexts, which is key to increasing generalization of communication skills (Ganz & Hong, 2014; Nunes & Hanline, 2007; Schepis, Reid, Behrmann, & Sutton, 1998). Further, a small number of studies indicated that AAC interventions implemented by varied communicative partners of people with ASD; including parents, peers, or classroom staff; may be as effective as implementation by researchers or specialists (Durand, 1999; McMillian, 2008; Nunes & Hanline, 2007; Park, Alber-Morgan, & Cannella-Malone, 2011; Sigafoos et  al., 2004; Trottier, Kamp, & Mirenda, 2011). This is critical to promoting generalization across communicative partners and contexts. Single-case studies investigating best practices in teaching caregivers and practitioners to implement AAC are needed (Ganz, Goodwyn, et al., 2013; Hong, Ganz, Gilliland, & Ninci, 2014). Unfortunately, research involving implementation across contexts and communicative partners is limited, so that effectiveness must be extrapolated based on existing research related to other developmental disabilities (Ganz & Hong, 2014). Lack of Evidence to Support Facilitated Communication Although, as noted above, several AAC interventions have empirical support, Facilitated Communication

(FC) has long been debunked (Todd, 2012) and use of FC has been demonstrated to result in harm; yet FC continues to be promoted by some service providers. FC involves having a facilitator provide ongoing physical support to the arm of the client using a keyboard or letter board (International Society on Augmentative and Alternative Communication [ISAAC], 2014). The person with complex communication needs reportedly selects the message with the emotional support of the facilitator. The research literature has clearly and repeatedly debunked facilitated communication, noting that the majority of the messages having been produced by the facilitator, or prompter, rather than the person with complex communication needs (Ganz, 2014; Mostert, 2001, 2010; Saloviita, Leppänen, & Ojalammi, 2014; Schlosser et al., 2014). That is, researchers have demonstrated that when the facilitator and the individual with complex communication needs are given separate stimuli, the message produced most frequently corresponds with the stimuli given to the facilitators (Bebko, Perry, & Bryson, 1996; Cabay, 1994; Hirshoren & Gregory, 1995; Kerrin, Murdock, Sharpton, & Jones, 1998). Further, in a number of cases, facilitated communication has been associated with false accusations of abuse of people with developmental disabilities, causing these individuals to be removed from their families (Gorman, 1999; Hostler, Allaire, & Christoph, 1993; Siegel, 1995). Notably, a former facilitator who was involved in a false abuse allegation case has disavowed the use of facilitated communication (Boynton, 2012). Given the potential dangers associated with this method, the lack of evidence of effectiveness, federal requirements for schools to implement evidence-based practices, and position statements from professional organizations (ISAAC, 2014), it is strongly recommended that practitioners and family members avoid use of FC. Implications of AAC and ASD Research for Practice Research is most useful when it can be translated into a form accessible to practitioners, family members, and other stakeholders. To that end, the sections that follow will address the implications of the AAC research on individuals with ASD related to: (a) selection of AAC modes, (b) the mobile technology revolution, (c) generalization of AAC and communication skills across communicative functions, varied outcomes, numerous contexts, and many communication partners, and (d) avoidance of unconventional and unproven AAC approaches. Selection of AAC Modes Parents and practitioners may have difficulty choosing what modes of AAC may be most suitable for their children or clients with ASD (Ganz, 2014). Certainly, the first step in determining the need for AAC and Augmentative and Alternative Communication

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State of the Science in AAC and ASD    5 selecting a method is to conduct a comprehensive assessment with a strong focus on communication skills and factors related to family and context (Ganz, 2014). Beyond assessment procedures, stakeholders may consider the literature related to matching characteristics of people with ASD to AAC, efficacy studies for AAC with people with ASD, and preference and choice studies. Aided AAC has been recommended as a good match, given that many individuals with ASD have difficulty understanding abstract concepts (e.g., spoken language), have strong interests in objects, and have challenging behaviors that occur due to problems with communicating (Durand, 1999; Ganz, Parker, & Benson, 2009; Ganz, Simpson, & Lund, 2012; Gernsbacher et  al., 2008). It does appear that, given the research to date and the core characteristics of ASD, aided AAC is a more efficacious means of providing a functional communication system to individuals with ASD than unaided AAC, or sign language (Ganz & Gilliland, 2014). Meta-analyses have begun to investigate matching characteristics, such as age and co-occurring disabilities, to particular modes of aided AAC (Ganz, Earles-Vollrath, et al., 2011; Ganz, Mason, et al., 2014). However, this work is in the early stages and additional studies with larger numbers of participants are needed before stakeholders may relate conclusions to particular individuals. It is likely that a multimodal communication approach is particularly effective in meeting the needs of people with ASD and complex communication needs across contexts (Light & Drager, 2007), although this has not been investigated in the AAC and ASD research to date. That said, it seems logical to provide multiple means of communicating, including use of multiple modes of AAC, speech approximations, gestures, and facial expressions (DeRuyter & Becker, 1988; Light, 1997). Thus, if a new means of communication is taught to address a challenging behavior that occurs when the individual is hungry, a laminated card with a picture and text stating, I’M HUNGRY, may be carried in the person’s pocket for easy access and use. In the classroom during read-aloud, the teacher may program a page on a mobile AAC app with hot spots that correspond with language related to a book being read that week. There may also be communication boards with a pictureexchange system throughout the classroom related to specific activities, such as a selection of art supplies in the art center. This same individual may also use some speech approximations to indicate yes and no in concert with nodding or shaking his or her head. To date, the literature has not indicated with confidence that individuals with ASD consistently select one particular mode of AAC (Ganz, Hong, & Goodwyn, 2013; van der Meer et  al., 2011). However, people with ASD often choose high-tech devices when offered speech-generating devices, exchange-based systems, or manual sign language (Couper et al., 2014; van der Meer et al., 2012). This pattern was the same when adult undergraduates were asked their perceptions of three © 2015 International Society for Augmentative and Alternative Communication

types of AAC (Achmadi et al., in press). That said, there are implications that can be drawn from the research on preference in AAC in people with ASD; clearly the preferences of the individual with ASD and his or her family members should be considered during the assessment process (Ganz, 2014). This may involve providing preliminary instruction in multiple forms of AAC, use of word approximations, and gestures and facial expressions, while collecting data to determine how quickly the individual is able to master multiple messages with each form of AAC (Cannella-Malone et al., 2009). Following this initial instruction, a preference assessment may be conducted, in which multiple modes of AAC may be placed in front of the individual and he or she may be asked to touch or pick up the preferred mode (van der Meer et al., 2012). Alternately, a preference assessment may be conducted during naturalistic communication opportunities, wherein a number of AAC modes are in reach, the placement of the modes is frequently randomized, and data are collected to determine how often the client selects each to communicate (Ganz, Hong, & Goodwyn, 2013). Implications of the Mobile Technology Revolution for AAC and Individuals with ASD Mobile devices are now ubiquitous in society (Gal et al., 2009; McNaughton & Light, 2013), and are also used by young children. There has been a rapid increase in the availability of AAC mobile apps for multiple operating systems (Gosnell, Costello, & Shane, 2011; McNaughton & Light, 2013). A few recent studies investigated the use of AAC mobile apps with people with ASD and offered promising results (Flores et al., 2012; Ganz, Hong, & Goodwyn, 2013; Kagohara et al., 2013; van der Meer et al., 2012). Such devices have a number of advantages over picture-exchange AAC and older stand-alone SGDs (Ganz, 2014). These include lower cost, which enables families to more easily access AAC (McNaughton & Light, 2013). These apps may be downloaded onto lightweight and small, yet powerful devices that can be easily transported across settings (Sennott & Bowker, 2009). Some people with ASD may be enticed to use dynamic mobile apps because they are appealing and associated with reinforcing activities (Ganz, Hong, & Goodwyn, 2013). Thus, these devices may be more appealing to family members due to the acceptability of mobile devices throughout the community (McNaughton & Light, 2013). Furthermore, the devices are easily programmable, which enables the individuals with ASD and his or her communicative partners to rapidly add vocabulary and personalize the system (Ganz, Hong, & Goodwyn, 2013). All of these factors may contribute to the increased use and acceptability of AAC (McNaughton & Light, 2013). Finally, when AAC is integrated within multifunction mobile technologies, individuals with ASD may have access to more diverse means to communicate as they can quickly refer to other apps and files (Hyatt, 2011).

6    J. B. Ganz

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Addressing Varied Communicative Functions, Outcomes, Contexts, and Communication Partners Although the majority of research on AAC for people with ASD has focused on teaching AAC use primarily for requesting items (Ganz, Earles-Vollrath, et  al., 2012), practitioners and family members should consider a wider range of communicative functions and other types of outcomes. A number of skills beyond requesting have been demonstrated to improve throughout AAC instruction (Ganz, Earles-Vollrath, et  al., 2012). For example, although family members may be hesitant to use AAC out of concern that speech would be inhibited (Romski & Sevcik, 2005), a meta-analysis and a systematic review have demonstrated the contrary – that speech is not negatively impacted and is sometimes improved over the course of AAC intervention (Ganz, Earles-Vollrath, et  al., 2012; Millar, Light, & Schlosser, 2006). While work remains to determine characteristics of children who may be most likely to gain speech concurrently with AAC intervention, it is safe to advise family members and practitioners that AAC will not be a detriment. Furthermore, AAC has been shown to be a viable intervention to treat both communication deficits and related challenging behaviors in people with ASD and complex communication needs (Ganz, Davis, et al., 2012; Ganz, Earles-Vollrath, et al., 2012; Ganz et al., 2009). This seems to be particularly true when AAC is implemented in conjunction with functional communication training, according to a recent metaanalysis (Walker & Snell, 2013). Behavior analysts may assist service providers in assessing the function of challenging behaviors and incorporating functional communication training into AAC interventions as needed (Durand, 1999). Finally, although research has not addressed a wide range of communicative functions beyond behavior regulation (e.g., protesting, requesting), it is clear that this lack of research also reflects a tendency among practitioners in the field to provide instruction in requesting skills to the exclusion of most other communicative functions (Ganz, Earles-Vollrath, et  al., 2012). Thus, it is imperative that service providers and family members provide instruction and opportunities to practice a range of communicative functions, including social interaction (e.g., sharing a social routing, greeting, showing off) and joint attention (e.g., sharing attention to items or information) (Shumway & Wetherby, 2009). Practitioners and family members should focus on providing AAC instruction and communication opportunities across all settings, contexts, and communicative partners that people with ASD and complex communication needs may encounter (Ganz & Hong, 2014). People with ASD frequently have difficulty generalizing skills to conditions under which they were not initially provided instruction. Therefore, it is critical for this population that instruction in any skill, particularly communication, which is used in all settings, is targeted in all

settings and contexts and with all possible communicative partners (Light, 1997; Ogletree, Davis, Hambrecht, & Phillips, 2012). Whether or not AAC skills are initially taught in didactic, highly structured contexts, they must quickly and repeatedly be addressed in other contexts. Service providers may use aspects of incidental teaching (Hart & Risley, 1978), or milieu teaching, to provide naturalistic instruction in AAC use to people with ASD, as well as providing instruction that may be mediated by their natural communicative partners (Trottier et al., 2011). Incidental AAC interventions require initiating communication opportunities or temptations, inserting communication within preferred activities or routines, using wait time to encourage communicative behaviors from the person with ASD and complex communication needs, and using cues and prompts to teach use of an AAC system (Ogletree et al., 2012). Avoidance of Unproven Treatments in AAC Although it is a common occurrence in the fields of medicine, allied health, and special education for practitioners and family members to adopt unsubstantiated treatments, it is not clear how to best educate and persuade practitioners and families to avoid unproven treatments such as FC. The rise of the Internet, although providing a means of gathering information, provides an apparently equal voice to unproven and to evidencebased practices, making it difficult for stakeholders to judge the accuracy and reliability of information. Service providers are frequently faced with the problem of how to discuss such issues with family members who may be swayed by sensational reports in popular and social media and online. Practitioners can try to persuade family members to use efficacious interventions by gently refusing to participate in implementation of unproven treatments and by providing family members with resources that direct them to rely on evidence-based practices. These include the National Standards Project of the National Autism Center (www.nationalautismcenter.org), the National Professional Development Center on Autism Spectrum Disorders (autismpdc.fpg.unc.edu), and the U.S. Department of Health and Human Services Interagency Autism Coordinating Committee (iacc.hhs.gov). A number of authors have discussed this issue at length in relation to unsubstantiated fad treatments for individuals with ASD, such as facilitated communication (Simpson et al., 2005). They suggest that practitioners (a) evaluate the originality of the message produced by facilitated communication (Konstantareas, 1998; Shane, 1994), (b) request that prompts and other physical supports and cues be faded quickly (Ganz, 2014), (c) consider the potential for harm resulting from false messages (e.g., false accusations of abuse, false attribution of skills or knowledge) (Simpson & Myles, 1995), and (d) consider the potential for wasted time or money that may be better spent on evidence-based practices (Simpson & Myles, 1995). Augmentative and Alternative Communication

State of the Science in AAC and ASD    7 Priorities for Future Research to Improve AAC Interventions for People with ASD Although great progress has been made in the quantity and quality of research on the implementation of AAC with people with ASD over the last several decades, critical work remains to maximize outcomes for individuals with ASD and complex communication needs and to best match individuals to particular AAC modes and intervention approaches. Research is required to evaluate the use of newly developed mobile AAC technologies and effective means of generalizing AAC skills across outcomes and contexts.

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Expansion of Research in Mobile Technologies Although preliminary efficacy studies have been conducted involving the implementation of AAC via mobile technology (Flores et al., 2012; Kagohara et al., 2013), additional research is needed. As AAC apps rapidly evolve, studies are needed to evaluate the efficacy of these apps and to compare mobile AAC apps and more traditional AAC systems (McNaughton & Light, 2013). In addition, although SGDs have frequently presented icons in grid array formats (Wilkinson & McIlvane, 2013), newer formats, such as visual scene displays, have been introduced. These displays use contextual scenes in the form of photographs or drawings to present in-context concepts (Wilkinson & Jagaroo, 2004). The images have hot spots that produce voice or sounds when selected or tapped (Wilkinson & Light, 2011). These scenes are thought to be more appropriate for young individuals with complex communication needs and those who are in the early stages of learning language concepts because they mimic the means by which typically-developing children learn language through contextual exposure (Drager, Light, Speltz, Fallon, & Jeffries, 2003; Light et al., 2004). Although research on this approach has been conducted with typically developing young children (Drager et al. 2003; Light et al., 2004), future research is needed to investigate this format and other newer approaches with people with ASD and complex communication needs. Protocols and Interventions to Address Varied Skills and Generalization As noted previously, although deemed important by experts, research into AAC for individuals with ASD has frequently focused on addressing limited skills, in highly structured settings, with limited communication partners, and with participants with ASD of limited age range (Ganz, Earles-Vollrath, et al., 2012). Thus, future research should focus on the following areas. It should provide family members and practitioners with distinct protocols and curricula to address a range of communicative functions and skill areas. It should also address the feasibility and fidelity of such treatments, to ensure that they are implemented as intended and in a manner in which stakeholders find manageable. © 2015 International Society for Augmentative and Alternative Communication

Future research is needed to address how to best provide instruction that will generalize across natural contexts. In this research, borrowing from AAC research into other disability categories, such as intellectual and developmental disabilities, may assist the development and evaluation of treatment protocols, particularly for naturalistic AAC interventions. One means of increasing AAC use would be to promote multimodal AAC use. Providing multiple means of communication, as appropriate for particular contexts, may increase communication across the board (Light & Drager, 2007). This might include use of a mobile AAC app in the cafeteria and community, and use of an exchange-based system during lessons, with picture cards specifically related to educational content, and supplemented by speech approximations. Finally, there is a need for development and efficacy research that incorporates or packages communication interventions into protocols specifically designed to meet the unique needs of people with ASD and complex communication needs. A suitable protocol might include functional communication training, behavioral techniques, and naturalistic AAC instruction. Understudied Populations and Matching Characteristics to Interventions Studies are needed to address gaps in the research about people with ASD who have complex communication needs and to better match individual characteristics to AAC designs and intervention approaches. In particular, AAC intervention for adolescents and adults with ASD has been severely understudied and research is urgently needed to address this gap (Ganz, Earles-Vollrath, et al., 2012). Furthermore, future research should investigate the design of high-tech AAC systems, with a view to better matching the needs and strengths of people with ASD (Light & McNaughton, 2013). Specifically, research and app development should consider ease of use and the level of cognitive demand, type of display (e.g., visual scene displays that embed language within familiar contexts), and visual attention to AAC displays (Light & McNaughton, 2013, 2014; Wilkinson & Light, 2014). Finally, questions regarding what modes of aided AAC, what design elements of high-tech AAC, and what instructional protocols may be most appropriate for particular individuals with ASD should be investigated, in order to allow for individualization in AAC interventions based on characteristics and functioning level. Potential Methods to Address Research Questions about AAC for Individuals with ASD Meta-analyses are increasingly used to aggregate results of single-case experimental designs to evaluate effectiveness of interventions for people with disabilities (Parker, Vannest, & Davis, 2011), including AAC interventions for people with ASD (e.g., Ganz, Davis, et  al., 2012; Ganz, Rispoli, et  al., 2014). These techniques require

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8    J. B. Ganz use of effect size measures, so small-N studies may be aggregated to allow more confidence in determination of effectiveness. There is some controversy regarding the use of these measures in single-case research (Schlosser & Pennington, 2005). There is not yet one universally accepted method of meta-analysis that statisticians agree upon, due to problems meeting the assumptions of many of the proposed methods (Kratochwill et  al., 2013); however, single-case experts have noted that these methods are beginning to gain acceptance (Kratochwill et al., 2010). New effect sizes will continue to be evaluated for their usefulness in aggregation of small-scale research (Horner & Kratochwill, 2012). Indeed, metaanalyses of single-case experimental designs are currently increasing in publication rate, particularly related to AAC interventions including for people with ASD (e.g., Flippin, Reszka, & Watson, 2010; Ganz, Davis, et  al., 2012; Ganz, Earles-Vollrath, et  al., 2012; Ganz, Rispoli, et al., 2014; Hart & Banda, 2010; Schlosser & Lee, 2000; Walker & Snell, 2013). This is particularly important given that single-case research makes up a large proportion of intervention research for people with ASD. Much work remains in the development of and acceptability of meta-analytic tools to aggregate singlecase research findings. For one, new single-case effect sizes are continuing to be developed and recommended, and meta-analyses should be conducted using the most up-to-date measures of magnitude of effect (Parker et  al., 2011). Additionally, previous meta-analyses on AAC have not included evaluations of the quality of the design of the included studies, which is critical in establishing confidence in the results reported (Kratochwill et  al., 2010; Wendt & Miller, 2012). Future meta-analyses should include rigorous design quality criteria as well as established review protocols, such as those recommended by the Cochrane Collaboration or the Campbell Collaboration, to ensure adherence to high standards for conducting the review or meta-analysis (Schlosser, Wendt, & Sigafoos, 2007). Furthermore, a number of methods would allow more fine-grained analyses to determine for whom particular modes and protocols are best suited using current effect sizes in meta-analysis, such as encouraging singlecase researchers to publish additional studies involving the topics above, and funding and publication of large group studies involving a range of people with ASD across age ranges and geographic settings. Such expansion will require the support and funding from granting agencies.

Conclusion The recommendations offered here are ambitious, though possible, with sufficient time and resources. It is clear that the rapidly increasing prevalence of ASD (CDC, 2014) is taxing, and will continue to tax, school systems and adult service systems. In particular,

individuals with ASD and complex communication needs are at higher risk for relying on more services into adulthood (Branson & Demchak, 2009; Hamm & Mirenda, 2006). Thus, addressing communication deficits early and intensively via AAC is critical. The current state of the science related to AAC for individuals with ASD is promising, although much work remains both in terms of research and the provision of resources for people with ASD and their family members and service providers. Declaration of interest: The author reports no conflict of interest. The author alone is responsible for the content and writing of the paper. This work was supported by the Center on Disability and Development at Texas A&M University, a federally recognized University Center of Excellence in Developmental Disabilities. References Achmadi, D., van der Meer, L., Sigafoos, J., Lancioni, G. E., O’Reilly, M. F., Lang, R., … & Marschik, P. B. (2015). Undergraduates’ perceptions of three augmentative and alternative communication modes. Developmental Neurorehabilitation, 22–25. doi:10.3109/ 17518423.2014.962767. American Psychiatric Association (APA). (2013). Diagnostic and statistical manual (5th ed.). Washington, DC: Author. Anderson, C. J., Colombo, J., & Shaddy, D. J. (2006). Visual scanning and pupillary responses in young children with autism spectrum disorder. Journal of Clinical and Experimental Neuropsychology, 28, 1238–1256. doi:10.1080/13803390500376790 Bebko, J. M., Perry, A., & Bryson, S. (1996). Multiple method validation study of facilitated communication: II. Individual differences and subgroup results. Journal of Autism & Developmental Disorders, 26, 19–42. Blackstone, S. (2005). What are visual scene displays? Augmentative Communication News, 1. Retrieved from http://www.imakenews. com/aac-rerc/e_article000344804.cfm?x  b11,0,w Bonvillian, J. D., & Nelson, K. E. (1976). Sign language acquisition in a mute autistic boy. Journal of Speech and Hearing Disorders, 41, 339–347. Boynton, J. (2012). Facilitated communication—what harm it can do: Confessions of a former facilitator. Evidence-based Communication Assessment and Intervention, 6, 3–13. doi: 10.1080/17489539.2012.674680 Brady, N. C., Anderson, C. J., Hahn, L. J., Obermeier, S. M., & Kapa, L. L. (2014). Eye tracking as a measure of receptive vocabulary in children with autism spectrum disorders. Augmentative and Alternative Communication, 30, 147–159. doi:10.3109/0743461 8.2014.904923 Branson, D. & Demchak, M. (2009). The use of augmentative and alternative communication methods with infants and toddlers with disabilities: A research review. Augmentative and Alternative Communication, 25, 274–286. Cabay, M. (1994). Brief report: A controlled evaluation of Facilitated Communication using open-ended and fill-in questions. Journal of Autism & Developmental Disorders, 24, 517–527. Cannella-Malone, H., DeBar, R. M., & Sigafoos, J. (2009). An examination of preference for augmentative and alternative communication devices with two boys with significant intellectual disabilities. Augmentative & Alternative Communication, 25, 262– 273. doi:10.3109/07434610903384511 Carr, E. G. (1979). Teaching autistic children to use sign language: Some research issues. Journal of Autism and Developmental Disorders, 9, 345–359. Augmentative and Alternative Communication

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in Developmental Disorders, 33, 406–418. doi:10.1016/j. ridd.2011.09.023. Ganz, J. B., Earles-Vollrath,T. L., Heath, A. K., Parker, R. I., Rispoli, M. J., & Duran, J. B. (2012). A meta-analysis of single case research studies on aided augmentative and alternative communication systems with individuals with autism spectrum disorders. Journal of Autism and Developmental Disorders, 42, 60–74. doi:10.1007/ s10803-011-1212-2 Ganz, J. B., Earles-Vollrath, T. L., Mason, R. A., Rispoli, M. J., Heath, A. K., & Parker, R. I. (2011). An aggregate study of singlecase research involving aided AAC: Participant characteristics of individuals with autism spectrum disorders. Research in Autism Spectrum Disorders, 5, 1500–1509. doi:10.1016/j. rasd.2011.02.011 Ganz, J. B., & Gilliland, W. (2014). Sign language versus aided AAC. In J. B. Ganz (Ed.), Aided augmentative and alternative communication for people with ASD (pp. 127–138). In J. Matson (series ed.), Autism and Child Psychopathology Series. New York, NY: Springer. doi: 10.1007/978-1-4939-0814-1_9 Ganz, J. B., Goodwyn, F. D., Boles, M. B., Hong, E. R., Rispoli, M. J., Lund, E. M., & Kite, E. (2013). Impacts of PECS instructional coaching intervention on practitioners and children with autism. Augmentative and Alternative Communication, 29, 210–221. doi: 10.3109/07434618.2013.818058 Ganz, J. B. & Hong, E. R. (2014). AAC intervention mediated by natural communication partners. In J. B. Ganz (Ed.), Aided augmentative and alternative communication for people with ASD (pp. 77–93). In J. Matson (series ed.), Autism and Child Psychopathology Series. New York, NY: Springer. doi: 10.1007/978-1-4939-0814-1_6 Ganz, J. B., Hong, E. R., & Goodwyn, F. D. (2013). Effectiveness of the PECS Phase III app and choice between the app and traditional PECS among preschoolers with ASD. Research in Autism Spectrum Disorders, 7, 973–983. doi:10.1016/j.rasd.2013.04.003 Ganz, J. B., Mason, R. A., Goodwyn, F. D., Boles, M. B., Heath, A. K., & Davis, J. L., (2014). Interaction of participant characteristics and type of AAC with individuals with ASD: A meta-analysis. American Journal on Intellectual and Developmental Disabilities, 119, 516–535. doi: 10.1352/1944-7558-119.6.516 Ganz, J. B., Parker, R., & Benson, J. (2009). Impact of the Picture Exchange Communication System: Effects on commu­ nication and collateral effects on maladaptive behaviors. Augmentative and Alternative Communication, 25, 250–261. doi: 10.3109/07434610903381111 Ganz, J. B., Rispoli, M. J., Mason, R.A., & Hong, E. R. (2014). Moderation of effects of AAC based on setting and types of aided AAC on outcome variables: An aggregate study of single-case research with individuals with ASD. Developmental Neurorehabilitation, 17, 184–192. doi: 10.3109/17518423.2012.748097 Ganz, J. B., Simpson, R. L., & Lund, E. M. (2012). The picture exchange communication system (PECS): A promising method for improving communication skills of learners with autism spectrum disorders. Education and Training in Autism and Developmental Disabilities, 47, 176–186. Gernsbacher, M., Sauer, E., Geye, H., Schweigert, E., & Goldsmith, H. (2008). Infant and toddler oral- and manual-motor skills predict later speech fluency in autism. Journal of Child Psychology and Psychiatry, 49, 43–50. Gillespie-Smith, K., & Fletcher-Watson, S. (2014). Designing AAC systems for children with autism: Evidence from eye tracking research. Augmentative and Alternative Communication, 30, 160– 171. doi:10.3109/07434618.2014.905635 Gorman, B. J. (1999). Facilitated Communication: Rejected in science, accepted in court—a case study and analysis of the use of FC evidence under Frye and Daubert. Behavioral Sciences & the Law, 17, 517–541. Gosnell, J., Costello, J., & Shane, H. (2011). Using a clinical approach to answer, “What communication apps should we use?” Perspective on Augmentative and Alternative Communication, 20, 87–96. doi: 10.1044/aac20.3.87 Hamm, B., & Mirenda, P. (2006). Post-school quality of life for individuals with developmental disabilities who use AAC.

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