ABSTRACT
Background
Technology-based AAC interventions have become increasingly available for people with aphasia (PWA). These interventions include speech generating devices (SGDs) and/or mobile technology applications or software programs that produce speech output upon selection of a message.
Aims
The purpose of this scoping review is to outline the current research evidence related to the effectiveness of AAC interventions using speech output technologies for PWA; identify gaps in the current literature; and propose directions for future research. To be included in this review, studies had to meet the following inclusion criteria: (a) the study’s intervention variables were related to the implementation of AAC using SGDs and/or mobile technology applications or software programs that turn computers into SGDs; (b) the studies included dependent variables which related to a change in behavior observed secondary to AAC intervention using speech-output technologies; (c) participants in the studies had a primary diagnosis of aphasia whose etiologies included, but were not limited to, stroke, TBI, and PPA (d) statistical data from group designs allowed for effect sizes to be calculated (i.e., Cohen’s d, Pearson’s product moment correlation coefficient r, partial eta-squared), and data from single-case experimental designs (SCEDs) allowed for Nonoverlap of All Pairs (NAP) to be calculated; (e) studies were published in peer reviewed journals, in English, and between the years 1990 and 2020.
Main Contributions
Our search methods yielded 16 pre-experimental and experimental studies that met our inclusion criteria. Effect sizes for functional communication outcome measures as well as behaviors related to symbol identification, symbol combination, and navigation of the AAC ranged from small to large for both SCEDs and group designs. Of the included experimental studies, only three were appraised as providing conclusive evidence. The remaining studies were appraised as providing preponderant (n=2), suggestive (n=2), and inconclusive (n=2) evidence.
Conclusion
Gaps in the research included limited data on generalization and maintenance across functional communication behaviors and communication environments. Future research must focus on discovering and understanding variables that lead to effective use of AAC strategies and techniques across communicative contexts and partners.
Supplementary material
Supplemental data for this article can be accessed online at https://doi.org/10.1080/02687038.2022.2135366
Disclosure Statement
No potential conflict of interest was reported by the authors.
Correction Statement
This article has been corrected with minor changes. These changes do not impact the academic content of the article.
Notes
1 Apple iPadTM are registered trademarks of the Apple Corporation, Cupertino, California, www.apple.com
2 Microsoft SurfaceTM is a product of Microsoft Corporation of Redmond, Washington., https://www.microsoft.com/en-us/
3 Android is a registered trademark of Google, Palo Alto, California, USA.
4 C-Speak Aphasia, DynavoxTM Vmax and DynaMyte 3100 are products of the DynaVox Mayer-Johnson Company of Pittsburgh, Pennsylvania., https://us.tobiidynavox.com
5 SentenceShaper® is a legal trademark of Psycholinguistic Technologies, Inc. of Jenkintown, Pennsylvania.
6 Portable Communication Assistant for people with Dysphasia is a product of Lingraphica of Princeton, New Jersey, https://www.aphasia.com
7 Gus is a product of Gus Communication Devices of Scottsdale, Arizona, https://usaspeechtablets.com
8 Talking Screen software is a product of Words+ Inc of Palmdale, California.