When measuring participant-reported attitudes and outcomes in the behavioral sciences, there are many instances when the common measurement assumption of unidimensionality does not hold. In these cases, the application of a multidimensional measurement model is both technically appropriate and potentially advantageous in substance. In this paper, we illustrate the usefulness of a multidimensional approach to measurement using an empirical example taken from the Behavior Change Consortium. Data from the Treatment Self-Regulation Questionnaire have been analyzed to investigate whether self-regulation can be regarded as a single construct, or if it has multiple dimensions based on the type of regulation or motivation that participants say helps them consider an improvement in healthy behavior. Comparison with consecutive analyses shows the advantages of multidimensional measurement for interpreting participant-reported data.