Identifying Mechanisms of Behavior Change in Psychosocial Alcohol Treatment Trials: Improving the Quality of Evidence from Mediational Analyses

Abstract

Objective: In recent years, a shift has occurred from identifying variables that mediate the effects of psychosocial interventions for problematic alcohol use to trying to identify effective mechanisms of behavior change (MOBCs) that lead to better drinking-related and other outcomes. Although implementing interventions targeting specific MOBCs has considerable conceptual and intuitive appeal, it is important that strong empirical evidence be available that supports such implementation. One aim of this article is to consider some prior mediational analyses of the effects of alcohol-focused psychosocial treatments to illustrate findings and the types of evidence that typically have been presented. A second aim is to consider methodological approaches, specifically certain statistical analyses of observational data and experimental designs, that could provide more rigorous evidence regarding the causal effects of mechanisms of change (mediators) in producing desired drinking-related outcomes.

Results: Prior analyses that have examined the association of a mediator with an outcome, or the relationship between a mediator and an outcome with assigned treatment controlled, do not provide strong evidence regarding the causal effects of mediators on outcomes. Unfortunately, experimental designs that directly manipulate mediators seem difficult to apply in the alcohol treatment field as an approach to examine mediator/MOBC effects.

Conclusion: To produce more compelling evidence, we need to investigate interventions that target a specific MOBC and then capitalize on random assignment to intervention/control conditions by using principal stratification or instrumental variable analyses to identify the effects of intervention-induced mediator change on outcomes.

Figure 1.

The basic mediational model. Note: Indirect effect of T on O via M = ab; direct effect of T on O = c′ = (c − ab); total effect of T (c) on O = indirect effect (ab) + direct effect (c′)

Figure 2.

Assumptions for instrumental variable (IV) analyses. Note: Assumptions of this type of IV analysis are that (a) the IV is strongly associated with the mediator, (b) the effect of the IV on the outcome is solely through the mediator, and (c) the IV is associated with no variable affecting the outcome other than the mediator.