Mediators, Moderators, and Covariates: Matching Analysis Approach for Improved Precision in Cognitive-Communication Rehabilitation Research

Abstract

Purpose: The dual goals of this tutorial are (a) to increase awareness and use of mediation and moderation models in cognitive-communication rehabilitation research by describing options, benefits, and attainable analytic approaches for researchers with limited resources and sample sizes and (b) to describe how these findings may be interpreted for clinicians consuming research to inform clinical care.

Method: We highlight key insights from the social sciences literature pointing to the risks of common approaches to linear modeling, which may slow progress in clinical-translational research and reduce the clinical utility of our work. We discuss the potential of mediation and moderation analyses to reduce the research-to-practice gap and describe how researchers may begin to implement these models, even in smaller sample sizes. We discuss how these preliminary analyses can help focus resources for larger trials to fully encapsulate the heterogeneity of individuals with cognitive-communication disorders.

Results: In rehabilitation research, we study groups, but we use the findings from those studies to treat individuals. The most functional clinical research is about more than establishing only whether a given effect exists for an "average person" in the group of interest. It is critical to understand the active ingredients and mechanisms of action by which a given treatment works (mediation) and to know which circumstances, contexts, or individual characteristics might make that treatment most beneficial (moderation).

Conclusions: Increased adoption of mediation and moderation approaches, executed in appropriate steps, could accelerate progress in cognitive-communication rehabilitation research and lead to the development of targeted treatments that work for more clients. In a field that has made limited progress in developing successful interventions for the last several decades, it is critical that we harness new approaches to advance clinical-translational research results for complex, heterogeneous groups with cognitive-communication disorders.

Figure 1.

Relationships of variables to the independent variable (X) and dependent variable (Y). The causal pathway is in black. Mediators (M) lie on the causal pathway, such that X affects M, which then affects Y, and are mechanisms driving the relationship between X and Y (e.g., why a treatment works). Moderators affect the size or direction of the relationship between X and Y and determine the contexts in which X affects Y (e.g., under what circumstances or for what types of people). Covariates explain some of the variability in Y but are not related to X or on the causal pathway. Confounders drive variability in both X and Y but do not drive the relationship between them. Adapted from Field-Fote (2019) with permission of Wolters Kluwer Health, Inc.

Figure 2.

(A) A standard linear model, in which the independent variable (X) affects the dependent variable (Y), and researchers adjust for a covariate (M). (B) If M explains part of the relationship between X and Y, it is on the causal pathway and should be treated as a mediator, not adjusted for as a covariate.

Figure 3.

The moderation model. The moderator, W, determines the direction or magnitude of the effect of independent variable X on dependent variable Y.

Figure 4.

Analytic pathways in the mediation model.