Input–output symmetry: why it matters for AAC users, and a word list to help

Child output = speech

Adult input = speech

Child output = AAC

Adult input = speech……. Whoops!? See how that might be a problem for learning?

How about:

Child output = AAC

Adult input = aided input (pointing to graphic symbols during speech)

“Among children with complex communication needs, vocabulary selection for aided AAC has almost exclusively been driven by consideration of expressive language needs. However, receptive language is critical to expres.png

No matter a child’s mode(s) of expressive communication, it’s our job to help ensure that they are getting receptive examples that match their expressive output, as often as possible. How? Encourage parents to use aided input, right? Simple!

Not simple. Consider this—are the words the family uses most frequently on the child’s device? Often times children’s AAC is programmed only for the child’s lexicon. But shouldn’t it also be set up for the words s/he is learning?

To help tackle the input–output asymmetry issue, this paper provides a list of words you may want to consider for programming young clients’ communication systems. The list is a compilation and comparison of data from three large sets, identifying words mothers use most frequently when speaking to their toddlers, as well as words most commonly spoken by toddlers and preschoolers.

They found that just over 250 words comprise most of mothers’ child-directed speech, with considerable overlap between mothers’ most frequent words and the words used by children (and this includes children unrelated to the mothers!… but arguably from similar cultural backgrounds). Another interesting finding: some mothers talk more than others (like, four times more), but the difference in lexical diversity among mothers (that is, number of different words) isn’t so high.

Though limitations include the fact that this research was done on typically-developing children, and it’s a new analysis of a ton of old data (from the late 80s forward), it “…provides a beginning place for guiding vocabulary selection.” So, basically, this list could be very useful as long as you take generational and cultural considerations in mind. So maybe add words like “tablet”? And please just ignore the fact that the data is on “mothers”, not parents in general—the world wasn’t as woke 20 years ago. 

This review is published in both the Early Intervention & Preschool & School-Age sections. 

Quick, N., Erickson, K., Mccright, J. (2019). The most frequently used words: Comparing child-directed speech and young children's speech to inform vocabulary selection for aided input. Augmentative and Alternative Communication. doi: 10.1080/07434618.201

Note: You can also find a link to this research at the author’s institutional repository, here.

And more...

Esmaeeli et al. found that family history is the biggest predictor of reading disorders in children at the end of second grade, but emergent literacy and oral language skills also played a role. As SLPs, we should always be taking family history into account when screening or testing for reading disorders.

Two studies this month looked at standardized language tests for Spanish–English bilingual children. Fitton et al. studied the sentence repetition task from the Bilingual English–Spanish Assessment (BESA) and found that it was a valid measure of morphosyntax in both Spanish and English. Wood & Schatschneider studied the Peabody Picture Vocabulary Test (PPVT-4) and found that it was biased against Spanish–English dual language learners (see also this review).

Méndez & Simon-Cereijido looked at Spanish–English bilingual preschoolers with developmental language disorder* (DLD) and found that children with better Spanish vocabulary skills also had better English grammar skills. They suggest targeting vocabulary in students’ home language to support English learning.

In a survey of nearly 3000 children, Reinhartsen et al. found that children with autism are significantly more likely to have higher expressive language skills than receptive. Children with this profile tended to have more severe delays and more significantly impaired language overall compared to children without this profile.

Rudolph et al. studied the diagnostic accuracy of finite verb morphology composite (FVMC) scores. Unlike previous studies, they found that FVMC wasn’t good at identifying 6-year-olds with developmental language disorder (DLD). The difference might be due to a larger, more representative sample of children. (NOTE: “The FVMC is derived from a spontaneous language sample, in either a free-play or elicited narrative scenario, and reflects the percent occurrence in obligatory contexts of eight T/A morphemes: regular past tense –ed, 3S, and present tense uncontracted and contracted copula and auxiliary BE forms (am, is, are).” ~Rudolph et al., 2019)

Verschuur et al. studied two types of parent training in Pivotal Response Treatment (PRT), finding that both group and individual training improved parents’ ability to create communication opportunities and increased children’s initiations. Furthermore, group training had additional benefits for parents’ stress levels and feelings of self-efficacy. The authors suggest that combining group and individual sessions might be a good way to build parents’ skills while conserving resources.

Venker et al. surveyed SLPs about their use of telegraphic speech. The vast majority of SLPs reported using telegraphic input for commenting on play, prompting for verbal imitations, and giving directions. However, only 18% of SLPs reported that they felt telegraphic speech is useful, which doesn’t make much sense! More research is needed to help align SLP practices and perspectives for use of telegraphic input. (Editors’ note = Perhaps it’s just a habit that’s hard to break? Even culturally influenced?)

 

*Note: The children in this study were those with Specific Language Impairment (SLI), which refers to children with Developmental Language Disorder (DLD) and normal nonverbal intelligence. We use DLD throughout our website for consistency purposes (read more here).

 

Esmaeeli, Z., Kyle, F.E., & Lundetræ, K. (2019). Contribution of family risk, emergent literacy and environmental protective factors in children’s reading difficulties at the end of second-grade. Reading and Writing. doi:10.1007/s11145-019-09948-5.

Fitton, L., Hoge, R., Petscher, Y., & Wood, C. (2019). Psychometric evaluation of the Bilingual English-Spanish Assessment sentence repetition task for clinical decision making. Journal of Speech, Language, and Hearing Research. doi:10.1044/2019_JSLHR-L-1

Méndez, L. I., & Simon-Cereijido, G. (2019). A view of the lexical-grammatical link in young latinos with specific language impairment using language-specific and conceptual measures. Journal of Speech, Language, and Hearing Research. doi:10.1044/2019_JSLHR-L-18-0315

Reinhartsen, D.B., Tapia, A.L., Watson, L., Crais, E., Bradley, C., Fairchild, J., Herring, A.H., & Daniels, J. (2019). Expressive dominant versus receptive dominant language patterns in young children: Findings from the study to explore early development. Journal of Autism and Developmental Disorders. doi:10.1007/s10803-019-03999-x

Rudolph, J. M., Dollaghan, C. A., & Crotteau, S. (2019). Finite verb morphology composite: Values from a community sample. Journal of Speech, Language, and Hearing Research. doi:10.1044/2019_JSLHR-L-18-0437 

Venker, C.E., Yasick, M., & McDaniel, J. (2019). Using telegraphic input with children with language delays: A survey of speech-language pathologists’ practices and perspectives. American Journal of Speech–Language Pathology. doi:10.1044/2018_AJSLP-18-0140

Verschuur, R., Huskens, B. & Didden, R. (2019). Effectiveness of Parent Education in Pivotal Response Treatment on Pivotal and Collateral Responses. Journal of Autism and Developmental Disorders. doi:10.1007/s10803-019-04061-6

Wood, C., & Schatschneider, C. (2019). Item bias: Predictors of accuracy on Peabody Picture Vocabulary Test-Fourth Edition items for Spanish-English-speaking children. Journal of Speech, Language, and Hearing Research. doi: 10.1044/2018_JSLHR-L-18-0145  

Training natural communication partners how to model AAC

Model, model, model! We all know how important and effective AAC modeling can be (see here and here, for example)—however, modeling is only as good as the partners who are implementing it. If you’re working with kids who use AAC, chances are there are communication partners who need guidance in how to model, and that’s no simple task. If you’re thinking “I agree, but HOW do I teach the partners?”, this review is for you!

The authors of this study gathered 29 studies in which more than 250 communication partners (including peers, teachers, paraprofessionals, parents, and other adults) implemented modeling strategies across various settings. Although they looked at a handful of research questions, the most clinically relevant questions were: How were the communication partners trained and what did they have to say about the training they received?

The most common training strategies were:

  • orally sharing information

  • modeling the strategies, and

  • allowing the partners to practice in controlled settings (role plays), or with a child, while providing feedback

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Overall, partners rated instruction as worth the time, easy to understand, practical, and transferable to other children. Some additionally offered the suggestion to provide more direction on how to model during a child’s regularly occurring activities (something to consider when you are providing training).

Seems pretty straightforward, right? We train the partners using those strategies and then off they go? Not so fast. The authors found that most communication partners also benefited from simultaneous support while learning to model. So after you train the partners, it’s important that you stick around to offer coaching and consultation as necessary.

If this seems daunting (how can I possibly fit this into my already jam-packed day!?), it’s important to remember that teaching communication partners can drastically improve the reach of our interventions—the amount of time we spend with our students is so limited compared to their interactions with natural communication partners.

If partner instruction is something you’d like to improve, be sure to check out the full article (specifically Table 2) for a list of the included studies and the training strategies used in each.

 

Biggs, E. E., Carter, E. W., & Gilson, C. B. (2019). A scoping review of the involvement of children's communication partners in aided augmentative and alternative communication modeling interventions. American Journal of Speech–Language Pathology. doi: 10.1044/2018_AJSLP-18-0024

Mistakes preschoolers make in multi-symbol utterances using AAC

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Preschoolers learning to communicate via AAC systems typically start by using one symbol at a time. Many go on to construct 2–3 symbol utterances, but make mistakes along the way. In this study, the researchers looked back at data from a prior study to explore 10 three–four-year-olds’ errors when producing multi-symbol utterances. In total, they made errors on 45% of their utterances!

We’ll get to those errors, but first, some background. All the preschoolers had a speech sound disorder/delay diagnosis, although one child also had a secondary ASD diagnosis and another was diagnosed with cerebral palsy. During the intervention sessions, the kids used an AAC device (an iPad with Proloquo2Go) to describe videos, then the clinician briefly modeled the targets and facilitated play-based therapy for 20 minutes. Keep in mind that the preschoolers didn’t have access to the device outside of the study, and 8 of the 10 participants actually had no prior experience with AAC before the intervention.  

Because AAC literature has focused heavily on inversions (word order reversals), the researchers checked for other error patterns.

 
The Complexity Approach for Grammar_.png
 

The main takeaway? Inversions and omissions were more common than substitutions and additions overall, but there were differences across targets and—business as usual for AAC studies—there were differences across the children in the study.

So, what can we do with this information? For starters, when you collect data, think beyond the number of words in the utterance. Instead, try classifying the types of errors the students are making. Are they inversions, substitutions, omissions, or additions? We’d wager that you’d approach instruction just a little bit differently depending on the error type—and that type of modification to your instruction could make all the difference!

FYI: As we mentioned, data analyzed here was originally collected for a different study. Although the data set isn’t perfect, this is the first study we have that conceptualizes the errors these children might be making. Also, keep in mind these targets were chosen specifically for speakers of English, which has a Subject + Verb  + Object syntax structure.

 

Binger, C., Richter, K., Taylor, A., Williams, E. K., & Willman, A. (2019). Error patterns and revisions in the graphic symbol utterances of 3- and 4- year old children who need augmentative and alternative communication. Augmentative and Alternative Communication. doi:10.1080/07434618.2019.1576224

AAC carryover: Buy-in is only the beginning

One of the biggest frustrations for clinicians who support AAC are the devices that don’t get used. You know, the ones that sit in the cabinet unless you’re in the room, or the ones that parents ask you not to send home. There are a lot of factors that contribute to this kind of device abandonment (can’t you just picture a lonely device feeling sorry for itself?). We need to understand these factors, so we can focus our work on the key ingredients that will promote AAC device use and help students—and their support teams—be successful.  

You won’t be surprised by two of the most common caregiver-related barriers to device success: 

1)    The adults don’t know how to use the device (or, they lack operational competency).

This includes finding words, programming, troubleshooting, and navigating the device settings. Parents and teachers often report that they don’t get enough training in this stuff.

2)    The adults don’t have positive attitudes about the device (or, they lack buy-in).  

Specific aspects of buy-in can include considering the device the child’s voice and believing that it should be available at all times.

These two barriers are important, for sure, but how important? And what else are we missing? This study delved into this issue, focusing on the operational competency and buy-in of parents and teachers of school-aged (3–16 years) children with autism, and whether they related to how frequently the children’s AAC devices were used. The 33 children in the study all used a personally-owned PRC device or the related LAMP Words for Life app as their main method of communication at both home and school. To measure how much devices were used, the researchers analyzed data from PRC’s Realize Language feature across three school days and one weekend. Parent and teacher surveys were used to measure operational competency and buy-in.

The good news? Overall, buy-in and operational competency was high for everyone. The bad news? No one was using devices that much. In this group, teachers reported greater buy-in (or at least answered their surveys that way, but that’s a whole different topic...), but parents and teachers were equally comfortable operating the devices. The devices were used more frequently at school vs. home (over half of the kids didn’t use the devices at home at all). 

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A big grain of salt here: the study looked at really a pretty small window in time (Is one weekend at your house representative of how your family works?), and only one device company—that uses a relatively complex language system—was in the mix. We also don’t know if looking at students with diagnoses other than autism would make a difference. Even so, it’s clear that something’s going on here. We can see that good intentions, valuing the device, and being trained in its use just isn’t enough. It looks like we need a broader conversation about barriers, including the practicalities of incorporating a device into daily activities and routines, especially at home. We definitely need to address operational competency and buy-in, but our families and other stakeholders are likely to need more support than that. The authors remind us to keep communication at the center of the conversation, rather than the technology. After all, the device is only the tool—communication is the point.

 

DeCarlo, J., Bean, A., Lyle, S., & Cargill, L. P. M. (2019). The Relationship Between Operational Competency, Buy-In, and Augmentative and Alternative Communication Use in School-Age Children With Autism. American Journal of Speech-Language Pathology. doi:10.1044/2018_AJSLP-17-0175

And more...

  • Accardo and colleagues provide an overview of effective writing interventions for school-age children with ASD. Most interventions took place in the classroom and used mixed approaches, combining “ingredients” like graphic organizers, video modeling, and constant time delay—a prompting strategy borrowed from ABA. Within the review, Tables 1 and 2 give an idea of what each one looked like, so check that out.

  • Baker & Blacher assessed behavior and social skills in 187 13-year-olds with ASD, intellectual disabilities (ID), or both. They found that having ID along with ASD was not associated with more behavior problems or less developed social skills as compared with ASD only.

  • Cerdán et al. found that eighth graders who had poor comprehension skills correctly answered reading comprehension questions more often when the question was followed by a rephrased, simplified statement telling them exactly what they needed to do.

  • Curran et al. found that preschool-aged children who are DHH and receive remote microphones systems in their homes have significantly better discourse skills (but no better vocabulary or syntax skills) than otherwise-matched children who don’t get those systems.

  • Facon & Magis found that language development, particularly vocabulary and syntax comprehension, does not plateau prematurely in people with Down Syndrome relative to people with other forms of intellectual disability. Language skills continue to show growth in both populations into early adulthood. (We’ve previously reviewed specific interventions that have resulted in language gains among older children and teens with Down Syndrome. )

  • Hu et al. suggest that computer-assisted instruction (CAI) can improve matching skills in school-age children with autism and other developmental disabilities. Although techy and exciting, CAI on its own isn’t enough—evidence-based instructional strategies like prompting and reinforcement have to be programmed in, too. This CAI used discrete trial training, and was more efficient (fewer prompts and less therapy time were needed for mastery!) than a traditional, teacher-implemented approach with flashcards.

  • Lim et al. found that the literacy instruction program MULTILIT was effective with school-age children with Down syndrome. MULTILIT combines phonics and sight word recognition instruction, geared toward children with students who are “Making Up Lost Time in Literacy” (MULTILIT; get it?). The program was implemented 1:1 for 12 weeks, and the students made gains in phonological awareness, word reading and spelling. MULTILIT has been investigated by the developers, but this is the first time it’s been studied by other researchers—and with kids with Down syndrome in particular.  Note: This article wasn’t fully reviewed because the training (provided only in Australia) is not available to the majority of our readers.

  • Muncy et al. surveyed SLPs and school psychologists and found that, in general, these professionals are underprepared to assess and treat children with hearing loss and other, co-occurring disabilities, and that they lack confidence in this area. Participants reported many barriers to valuable collaboration with other professionals, like audiologists (hint: there aren’t enough of them!), and that they want more training in this area.

  • Schlosser et al. found that 3–7 year old children with ASD accurately identified more animated symbols than static symbols. The animated symbols represented verbs; for example, depicting a person turning around versus a still line drawing of “turn around.” It makes sense to see action verbs—well—in action; however, researchers acknowledge we can’t make grid displays full of animated symbols since that could be overstimulating. The next step is to test the effects of animation on symbol identification with other more well-known symbols sets like PCS.

  • Scott et al. used science books and a signed dialogic reading program with an 11-year-old Deaf student, and found increases in the student’s ability to answer comprehension questions.

  • St John et al. found that 92% of their sample of children and adolescents with Klinefelter syndrome also had a communication impairment. Pragmatic, language, and literacy impairments were common, and the researchers described some speech impairments as well. Establishing a comprehensive communication profile for this group is important because we’re still learning about Klinefelter syndrome, which is caused by one or more extra X chromosomes.

  • Updates on PEERS, a structured social skills program for adolescents and young adults we’ve discussed before! Wyman & Claro used the school-based version of PEERS both with adolescents with ASD (the target audience) and those with intellectual disabilities (ID; an overlooked group in social skills research who may benefit nonetheless). Both groups of students improved their social knowledge, and the ID group (but not the ASD group) increased social interactions with friends outside of school. Meanwhile, Matthews et al. found that speeding up the traditional, clinic-based PEERS program, by offering it in 7 weeks (twice weekly sessions) instead of 14, didn’t reduce its effectiveness.

Accardo, A. L., Finnegan, E. G., Kuder, S. J., & Bomgardner, E. M. (2019). Writing Interventions for Individuals with Autism Spectrum Disorder: A Research Synthesis. Journal of autism and developmental disorders, 1-19. doi:10.1007/s10803-019-03955-9

Baker, B. L., & Blacher, J. (2019). Brief Report: Behavior Disorders and Social Skills in Adolescents with Autism Spectrum Disorder: Does IQ Matter? Journal of Autism and Developmental Disorders. doi:10.1007/s10803-019-03954-w

Cerdán, R., Pérez, A., Vidal-Abarca, E., & Rouet, J. F. (2019). To answer questions from text, one has to understand what the question is asking: Differential effects of question aids as a function of comprehension skill. Reading and Writing. doi:10.1007/s11145-019-09943-w

Curran, M., Walker, E. A., Roush, P., & Spratford, M. (2019). Using Propensity Score Matching to Address Clinical Questions: The Impact of Remote Microphone Systems on Language Outcomes in Children Who Are Hard of Hearing. Journal of Speech, Language, and Hearing Research. doi:10.1044/2018_JSLHR-L-ASTM-18-0238

Facon, B., & Magis, D. (2019). Does the development of syntax comprehension show a premature asymptote among persons with Down Syndrome? A cross-sectional analysis. American Journal on Intellectual and Developmental Disabilities. doi: 10.1352/1944-7558-124.2.131

Hu, X., Lee, G. T., Tsai, Y, Yang, Y., & Cai, S. (2019). Comparing computer-assisted and teacher-implemented visual matching instruction for children with ASD and/or other DD. Journal of Autism and Developmental Disorders. doi:10.1007/s10803-019-03978-2

Lim, L., Arciuli, J., Munro, N., & Cupples, L. (2019). Using the MULTILIT literacy instruction program with children who have Down syndrome. Reading and Writing. doi:10.1007/s11145-019-09945-8

Matthews, N. L., Laflin, J., Orr, B. C., Warriner, K., DeCarlo, M., & Smith, C. J. (2019). Brief Report: Effectiveness of an Accelerated Version of the PEERS® Social Skills Intervention for Adolescents. Journal of Autism and Developmental Disorders. doi:10.1007/s10803-019-03939-9

Muncy, M. P., Yoho, S. E., & McClain, M. B. (2019). Confidence of School-Based Speech-Language Pathologists and School Psychologists in Assessing Students With Hearing Loss and Other Co-Occurring Disabilities. Language, Speech, and Hearing Services in Schools. doi:10.1044/2018_LSHSS-18-0091

Schlosser, R. W., Brock, K. L., Koul, R., Shane, H., & Flynn, S. (2019). Does animation facilitate understanding of graphic symbols representing verbs in children with autism spectrum disorder? Journal of Speech, Language, and Hearing Research. doi:10.1044/2018_JSLHR-L-18-0243

Scott, J. A., & Hansen, S. G. (2019). Comprehending science writing: The promise of dialogic reading for supporting upper elementary deaf students. Communication Disorders Quarterly. doi:10.1177/1525740119838253

St John, M., Ponchard, C., van Reyk, O., Mei, C., Pigdon, L., Amor, D. J., & Morgan, A. T. (2019). Speech and language in children with Klinefelter syndrome. Journal of Communication Disorders. doi:10.1016/j.jcomdis.2019.02.003 

Wyman, J., & Claro, A. (2019). The UCLA PEERS School-Based Program: Treatment Outcomes for Improving Social Functioning in Adolescents and Young Adults with Autism Spectrum Disorder and Those with Cognitive Deficits. Journal of Autism and Developmental Disorders. doi:10.1007/s10803-019-03943-z

Diagnosing DLD when you don’t speak a child’s first language

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We know that it’s best to assess children in their first languages. But, we simply don’t have access to measures or interpreters for all of the world’s languages. What’s a monolingual SLP to do?

New research supports what we’ve discussed previously: that by using parent questionnaires and measures of language processing, we can accurately diagnose language disorders in English language learners using only English measures. Li’el et al. recruited a sample of bilingual and monolingual Australian English-speaking 5- to 6-year-old children with and without developmental language disorder (DLD). “Bilingual” was defined as hearing English less than half the time at home. Parents completed a questionnaire and children completed the CTOPP nonword repetition and CELF-P2 recalling sentences subtests.

The researchers found that the parent questionnaire alone had the highest sensitivity and specificity (accuracy at ruling in and ruling out DLD). However, all of the assessments in combination still had good diagnostic accuracy, and it’s not a good idea to diagnose a child with only one test, so the authors recommend using more than one measure.

Overall, this study adds to evidence that by interviewing parents and using language processing tasks, we can do a pretty good job teasing apart a lack of English exposure from an underlying language disorder even if we can’t assess in a child’s first language.

 

Li’el, N., Williams, C. & Kane, R. (2018). Identifying developmental language disorder in bilingual children from diverse linguistic backgrounds. International Journal of Speech-Language Pathology. Advance online publication. doi: 10.1080/17549507.2018.1513073

And more...

Chester et al. enrolled school-aged children with ASD in group social skills training that included play (unstructured or semi-structured) for 8 weeks. They found that participants gained social skills (as rated by parents, teachers, and the children themselves) compared to waiting controls.  

Conlon et al. looked at narratives (via the ERNNI) produced by 8-year-old boys and girls with ASD and average nonverbal intelligence. While we know that children with ASD often struggle with narratives in general, there may be important gender-related differences. This study found that girls’ stories were more complete, included more information about characters’ intentions, and were easier to follow (i.e. they had better referencing).

Joseph used word boxes (a low-tech method using drawn rectangles and letter tiles) to teach sound segmentation, word identification, and spelling skills to three third graders with autism, and found that all children improved on sound segmentation and word ID and two children improved on spelling. 

Montallana et al. studied inter-rater reliability of the VB-MAPP Milestones and Barriers assessments. The VB-MAPP is commonly used to assess and plan intervention for children with ASD, but we haven’t known much about its psychometrics. While the milestones section had largely moderate to good reliability, agreement between raters on barriers was poor to moderate.  

Thirumanickam et al. found that a video-based modeling intervention was effective in increasing conversational turn-taking in a small number of adolescents with ASD who used AAC—BUT, only when provided with additional instruction (least-to-most prompting). They stated that for students with ASD, some level of prompting is likely required to engage in video-based interventions.

 

Chester, M., Richdale, A. L., & McGillivray, J. (2019). Group-Based Social Skills Training with Play for Children on the Autism Spectrum. Journal of Autism and Developmental Disorders. Advance online publication. doi:10.1007/s10803-019-03892-7

Conlon, O., Volden, J., Smith, I. M., Duku, E., Zwaigenbaum, L., Waddell, C., … Pathways in ASD Study Team. (2019). Gender Differences in Pragmatic Communication in School-Aged Children with Autism Spectrum Disorder (ASD). Journal of Autism and Developmental Disorders. Advance online publication. doi:10.1007/s10803-018-03873-2

Joseph, L. M. (2018). Effects of word boxes on phoneme segmentation, word identification, and spelling for a sample of children with autism. Child Language Teaching and Therapy34(3), 303–317.

Montallana, K. L., Gard, B. M., Lotfizadeh, A. D., & Poling, A. (2019). Inter-Rater Agreement for the Milestones and Barriers Assessments of the Verbal Behavior Milestones Assessment and Placement Program (VB-MAPP). Journal of Autism and Developmental Disorders. Advance online publication. doi:10.1007/s10803-019-03879-4

Thirumanickam, A., Raghavendra, P., McMillan, J. M., & van Steenbrugge, W. (2018). Effectiveness of video-based modelling to facilitate conversational turn taking of adolescents with autism spectrum disorder who use AAC. Augmentative and Alternative Communication, 34(4), 311–322.

Parent-reported outcome measure: Measuring what counts in AAC therapy

What outcomes are you measuring in your AAC therapy? Frequency of initiation, purposes of communication, number of symbols mastered? All important, but are we forgetting something here?

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In order for AAC to be successful, it has to be valued by the family and be seen as improving the child’s participation in the family’s everyday life. Okay—so we all know this, but how do we actually measure and track these parent perceptions? Luckily, there is a (free!) parent-report outcome measure that can help. The Family Impact of Assistive Technology Scale for AAC (FIATS-AAC) is a relatively new tool that was developed to measure the impact of AAC on the lives of children and families.

This study found that the FIATS-AAC could capture improvements in children’s (3–17 years old) functioning—as rated by parents—in the first 6 and 12 weeks of therapy with a new device, with more change reflected in cases where the clinicians also noted progress. When change was expected to occur (as therapy progressed), the questionnaire was sensitive enough to show that change. Great data for your first periodic review? Parents and therapists on the same page? This is what we all want!

This tool is fairly new, but it can definitely be useful to SLPs looking for ways to involve families, identify important therapy outcomes, and measure short-term, meaningful change during AAC intervention.

Ready to take a closer look? You can access the questionnaire here for free!

 

Ryan, S. E., Shepherd, T. A., Renzoni, A. M., Servais, M., Kingsnorth, S., Laskey, C., ... & Bradley, K. (2018). Responsiveness of a parent-reported outcome measure to evaluate AAC interventions for children and youth with complex communication needs. Augmentative and Alternative Communication. Advance online publication. doi: 10.1080/07434618.2018.1520296