Background:

Augmentative and alternative communication (AAC) can mitigate the impact of communication disorders by providing an immediate mode for functional communication and visual supports to enhance comprehension while toddlers’ speech and language skills are developing (Light and McNaughton, 2012). Though AAC interventions improve children’s language, literacy, social, and adaptive skills, they are rarely initiated with toddlers during a critical period in language development (Guralnick, 2017). Timely provision of AAC intervention is vital because developing foundational functional communication and early symbolic skills are necessary to help toddlers learn vocabulary and transition to combining words (Light, et al, 2019). Caregivers of children with IDD often receive minimal instruction on AAC and supporting communication with their children at home (Baggett, et al., 2010). Without individualized, family-centered instruction, caregivers are unprepared to support AAC use and language learning at home. One promising method for expanding access to AAC intervention is teaching caregivers to use AAC and language facilitation strategies using hybrid (in-person and telehealth) models (Quinn, et al., 2021). Our goal is to understand caregivers’ preferences for an AAC intervention and the challenges of using AAC with toddlers at home. This knowledge is critical to the future success of AAC interventions because AAC interventions for toddlers lack robust social validation (Goldstein, 2016). Additionally, caregivers’ perceptions of intervention feasibility and acceptability impact intervention adoption.


Summary of Proposal:
The purpose of this study was to determine caregivers’ preferences and needs regarding two key AAC intervention components: (a) service delivery (b) strategies to enhance treatment adherence. As this research is preliminary, this poster presentation will highlight pertinent themes collected during the interview coding process. Additionally, this presentation will explore caregiver-identified barriers to successful AAC intervention implementation and discuss intervention features that may support successful outcomes in the home environment. This knowledge is critical to the future success of AAC interventions because caregivers’ perceptions of intervention feasibility and acceptability impact intervention adoption.


Purpose:
The purpose of this study was to determine caregivers’ preferences and needs regarding two key AAC intervention components: (a) service delivery and (b) strategies to enhance treatment adherence. In this project, treatment adherence strategies refer to the techniques, methods, and approaches that help family members use AAC systems and AAC intervention strategies at home. Examples may include text-message reminders, tip sheets, and caregiver instruction.


Method: 
A grounded theory approach (Corbin & Strauss, 2015) was used to collect and code caregiver interviews. Qualitative methods were applied to allow for in-depth, inductive, and dynamic exploration of factors that impact AAC use at home. Constant comparative analysis (Cresswell & Poth, 2018) was used to derive emergent themes.
Participants and setting: 
17 caregivers of children with IDD (24 – 58 months) who received early intervention services completed interviews conducted via a virtual platform. Purposive sampling strategies were used to recruit caregivers with diversity in social demographic characteristics.


Design and procedures: 
A semi-structured interview protocol was developed and revised with feedback. Questions inquired about caregivers’ global perceptions of AAC, experiences with community-based early intervention, preferences for strategies to increase treatment adherence, and preferences for service delivery. The researchers followed a three-step data processing method. First, the audio files were uploaded to Otter.Ai transcription service to prepare a verbatim transcript. Next, a researcher reviewed the entire transcription against the audio recording for accuracy and removed identifying details. Last, the cleaned transcripts were uploaded to NVivoR1.7.1 for analysis. Each interview transcript is being coded independently using an inductive and iterative process following the constant comparative method.

Results: 
Results are preliminary in nature as coding is currently in progress. Strong themes have emerged as coding has been conducted in both (a) service delivery and (b) strategies to enhance treatment adherence. Caregivers identified that in-person service delivery models promote: a) hands-on learning and caregiver self-efficacy, b) supports stronger relationships between therapist, child and caregiver (especially during the initial aspects of therapy), and c) removes the possibility of experiencing technical issues that can occur during telehealth. Caregivers identified that telehealth service delivery models promote: a) greater availability of speech-language pathologists, b) it often works better for direct parent-therapist interactions, and c) it can decrease domestic load (e.g., cleaning the house in preparation for a provider to visit, arranging schedules to be at home for the visit, etc). Caregivers identified several strategies that promoted greater adherence to treatment protocol and/or recommendations including: a) concrete and easily accessible information on AAC devices and sign language, b) videos of caregivers using AAC and sign language, c) connection with other caregivers, d) access to SLPs who have experience with AAC, and e) the ability to ask questions to between sessions. 

Discussion: 
The purpose of this study is to determine caregivers’ preferences and needs regarding two key AAC intervention components: (a) service delivery (b) strategies to enhance treatment adherence. As this research is preliminary, specific conclusions cannot be drawn to directly answer these two questions. However, some pertinent themes have been collected during the interview coding process. These themes include common caregiver-identified barriers to successful AAC intervention implementation and intervention features that may support successful outcomes in the home environment. 

References
Baggett, K. M., Davis, B., Feil, E. G., Sheeber, L. L., Landry, S. H., Carta, J. J., & Leve, C. (2010). Technologies for Expanding the Reach of Evidence-Based Interventions: Preliminary Results for Promoting Social-Emotional Development in Early Childhood. Topics in Early Childhood Special Education, 29(4), 226–238. https://doi.org/10.1177/0271121409354782


Corbin, J., & Strauss, A. (2015). Basics of qualitative research. Sage.


Chung, Y. C., & Stoner, J. B. (2016). A meta-synthesis of team members' voices: What we need and what we do to support students who use AAC. Augmentative and alternative communication, 32(3), 175–186. https://doi.org/10.1080/07434618.2016.1213766


Creswell, J.W. and Poth, C.N. (2018). Qualitative inquiry and research design choosing among five approaches. (4th ed.) Sage.


Dada, S., Flores, C., Bastable, K., & Schlosser, R. W. (2021). The effects of augmentative and alternative communication interventions on the receptive language skills of children with developmental disabilities: A scoping review. International journal of speech-language pathology, 23(3), 247–257. https://doi.org/10.1080/17549507.2020.1797165


Drager, K., Light, J., & McNaughton, D. (2010). Effects of AAC interventions on communication and language for young children with complex communication needs. Journal of pediatric rehabilitation medicine, 3(4), 303–310. https://doi.org/10.3233/PRM-2010-0141


Glaser, B. G., & Strauss, A. (1967). The discovery of grounded theory: Strategies for qualitative research. Aldine.


Goldstein H. Where does social validity measurement fit into identifying and developing evidence based practices?, Communication Interventions for Individuals with Severe Disabilites: 
Exploring Research Challenges and Opportunities. Brookes; 2016:299-312.


Guralnick M. J. (2017). Early Intervention for Children with Intellectual Disabilities: An Update. Journal of applied research in intellectual disabilities: JARID, 30(2), 211–229. https://doi.org/10.1111/jar.12233


Light, J., & McNaughton, D. (2012). The changing face of augmentative and alternative communication: past, present, and future challenges. Augmentative and alternative communication, 28(4), 197–204. https://doi.org/10.3109/07434618.2012.737024


Light, J., McNaughton, D., & Caron, J. (2019). New and emerging AAC technology supports for children with complex communication needs and their communication partners: State of the science and future research directions. Augmentative and alternative communication, 35(1), 26–41. https://doi.org/10.1080/07434618.2018.1557251


O’Brien, B. C., Harris, I. B., Beckman, T. J., Reed, D. A., & Cook, D. A. (2014). Standards for reporting qualitative research: A synthesis of recommendations. Academic Medicine, 89(9), 1245. https://doi.org/10.1097/ACM.0000000000000388


QSR International Pty Ltd. (2021) NVivo (released in December 2021). https://www.qsrinternational.com/nvivo-qualitative-data-analysis-software/home



Caregiver Preferences for Early AAC Intervention: Preliminary Themes and Reflections

Symmetries of Behavior in Social Performance Contexts

Finding Cause in Failure

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It Starts at Home: The Role of Parental Socialization on the Development of Gendered Speech

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Caregiver Preferences for Early AAC Intervention: Preliminary Themes and Reflections

Symmetries of Behavior in Social Performance Contexts

Finding Cause in Failure

Cognition in the fields of values

How does the syntax of counting affect learnability? Evidence from artificial language learning.

Expectation, Representation, and Enactivism

Emotion Recognition and Gaze Pattern of Preschool Children with Autism Spectrum Disorders Children

Story Reading and Children’s Gender Stereotype Representation

It Starts at Home: The Role of Parental Socialization on the Development of Gendered Speech

Discriminability of picture book typeface in children

How Speech and Representational Gestures Align in Child-Directed Language: a Corpus-based Study

Optimizing Random Sampling of Daylong Audio

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