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Predicting ReST outcomes: IPD meta-analysis (Ng et al., 2022)

posted on 29.04.2022, 17:03 by Wei Lin Ng, Patricia McCabe, Rob Heard, Veronica Park, elizabeth murray, Donna Thomas

Purpose: The purpose of this study is to identify predictors of treatment outcomes in Rapid Syllable Transition Treatment (ReST) for childhood apraxia of speech through an individual participant data meta-analysis.

Method: A systematic literature search identified nine ReST studies for inclusion. Individual participant data were obtained, and studies were coded for methodological design, baseline participant characteristics, service delivery factors, and treatment outcomes. Bivariate analyses were conducted to identify potential predictor variables. Multiple linear regressions were then performed to identify predictors of treatment outcomes.

Results: Data for 36 participants from seven studies were included in the statistical analyses. In multivariate modeling, better performance on treated pseudowords posttreatment was predicted by higher baseline expressive language and Goldman-Fristoe Test of Articulation scores, lower speech inconsistency and percentage of vowels correct, and higher pretreatment accuracy on pseudoword targets. Better performance on untreated real words posttreatment was predicted by higher pretreatment accuracy on real words. Gains in performance and retention of gains were not significantly predicted by any individual variable or combination of variables.

Conclusions: Baseline speech and expressive language skills and accuracy on pseudowords and real words were significant predictors of absolute posttreatment performance. Regardless of baseline characteristics, all children were statistically as likely to achieve gains during ReST and retain these gains for up to 4 weeks posttreatment. Large-scale prospective research is required to further examine the effects of dose frequency and co-occurring language impairments on treatment outcomes and the complex co-effects of percentage of vowels correct with other potential predictors.

Supplemental Material S1. Baseline variables and assessment tools.

Supplemental Material S2. Pearson’s correlation coefficients for potential predictor variables.

Supplemental Material S3. Quality ratings for included studies.

Supplemental Material S4. Suggested pretreatment assessment protocol.

Ng, W. L., McCabe, P., Heard, R., Park, V., Murray, E., & Thomas, D. (2022). Predicting treatment outcomes in rapid syllable transition treatment: An individual participant data meta-analysis. Journal of Speech, Language, and Hearing Research. Advance online publication. https://doi.org/10.1044/2022_JSLHR-21-00617