Abstract Functional communication training (FCT) is a widely used behavioral intervention for reducing challenging behavior for students with disabilities. As more students with disabilities are being served in educational settings, it is essential to understand and evaluate the evidence base of FCT in educational contexts. A clear synthesis of how FCT has been applied, by whom, under what conditions, and with what outcomes is needed to evaluate its evidence base and inform translational practice. This mega-review aggregated six systematic reviews and meta-analyses of FCT implemented in educational settings, following PRISMA guidelines. Data were extracted at the review level on participant characteristics (e.g., age, gender, race, disability), functional behavior assessment (FBA) methods and identified functions of behavior, interventionist roles, procedural components of FCT, methodological quality, and outcomes (behavioral change, communication, social validity), as well as documented recommendations. Findings revealed consistent positive effects of FCT on challenging behavior reduction, with variability in reported moderators (e.g., setting, communication modality, and implementer). Notable gaps included limited demographic reporting, overrepresentation of male participants, and variability in review rigor. Implications of this mega-review include the need for greater transparency in methodological reporting, inclusion of culturally responsive and demographically disaggregated data, and appropriate individualized modification of FBA and FCT implementation by natural change agents in educational settings to support generalization, maintenance, and equity.

Abstract Multilevel modeling is a promising approach that can be applied to evaluate intervention effectiveness and explain variability in intervention effectiveness in single-case experimental design research. This approach is recommended as it accounts for the nested data structure and allows to model complexities such as autocorrelation, nonlinear time trends and the inclusion of participant characteristics as moderators to account for variability in intervention effectiveness. Therefore, choices need to be made to select the most appropriate multilevel model given the research question and the need to model (some or all) complexities. This brief commentary provides criteria that can be used to inform appropriate model selection and ends with a recommendation for best practices for model building. Our hope is to further enhance the understanding of the appropriateness and applicability of the multilevel modeling approach to analyze single-case experimental data.