Abstract
This meta-analysis examined communication outcomes in single-case design studies of augmentative and alternative communication (AAC) interventions and their relationship to participant characteristics. Variables addressed included chronological age, pre-intervention communication mode, productive repertoire, and pre-intervention imitation skills. Investigators identified 114 single-case design studies that implemented AAC interventions with school-aged individuals with autism spectrum disorder and/or intellectual disability. Two complementary effect size indices, Tau(AB) and the log response ratio, were applied to synthesize findings. Both indices showed positive effects on average, but also exhibited a high degree of heterogeneity. Moderator analyses detected few differences in effectiveness when comparing across diagnoses, age, the number and type of communication modes, participant’s productive repertoires, and imitation skills to intervention. A PRISMA-compliant abstract is available: https://bit.ly/30BzbLv.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Notes
1 Originally a third effect size metric, the between-case standardized mean difference was planned (BC-SMD; Hedges, Citation2013; Hedges et al., Citation2012; Pustejovsky et al., Citation2014). The primary advantage of the BC-SMD is that it expresses effect size magnitude on a scale that is comparable to the standardized mean difference that would be estimated from a between-group design conducted with the same population of participants, same intervention, and same outcomes. BC-SMDs also have several limitations, including that (a) they aggregate outcomes across participants and thus might conceal participant-level variation (Kratochwill & Levin, Citation2014); (b) their estimation methods are only available for multiple baseline, multiple probe, and treatment reversal designs that include at least three unique participants (Valentine et al., Citation2016); and (c) they are based on parametric assumptions that may not be appropriate and reasonable for some outcome data (Shadish et al., Citation2015). Based on visual inspection of outcome data graphs for this study, the modeling assumptions of the BC-SMD were determined to be inappropriate for the bulk of the included studies, due to the fact that studies predominantly used frequency counts or percentage measures of behavioral outcomes, for which modeling assumptions were implausible; thus, the analysis based on the BC-SMD was not executed.