Abstract
Behavioral, biobehavioral, and biomedical interventions presume a causal story. This causal story is used to create a conceptual model of why the intervention caused the observed outcome. Methods are needed to investigate the extent to which changes in the outcome are due to exposure to an intervention. This chapter describes the use of a factorial experiment in which an intervention’s components are varied, the mediating mechanisms and outcome are measured, and then an analysis is performed to investigate an intervention’s causal story. To illustrate the procedures, a case study examines an intervention guided by the model of stigma communication (MSC; Smith, Commun. Theory 17:462–485, 2007; Stigma communication and health. In T. L. Thompson, R. Parrott, & J. Nussbaum (Eds.), Handbook of health communication (2nd ed., pp. 455–468). London, UK: Taylor & Francis, 2011; Commun. Monogr. 79:522–538, 2012). In the case study, we show how to conduct a mediation analysis when four components of an intervention have been manipulated in a 24 factorial experiment (N = 299), and, in addition, four hypothesized mediators have been measured. We reflect on how the results provide more precise conclusions about the theory guiding the intervention and opportunities for refinement.
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Notes
- 1.
This story assumes that the intervention’s outcome can change. For example, if an intervention’s goal is to improve how often people wash their hands, then handwashing rates must be able to change.
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Acknowledgments
Our thanks go to John Dziak, two anonymous reviewers, and researchers at the Methodology Center for feedback on earlier drafts. This project was supported by several National Institutes of Health (NIH) awards: R21 HG007111 from the National Human Genome Research Institute, P50 DA010075 from the National Institute on Drug Abuse, P50 CA143188 from the National Cancer Institute, and R01 DK097364 from the National Institute of Diabetes and Digestive and Kidney Diseases. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH or its institutes.
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Smith, R.A., Coffman, D.L., Zhu, X. (2018). Investigating an Intervention’s Causal Story: Mediation Analysis Using a Factorial Experiment and Multiple Mediators. In: Collins, L., Kugler, K. (eds) Optimization of Behavioral, Biobehavioral, and Biomedical Interventions. Statistics for Social and Behavioral Sciences. Springer, Cham. https://doi.org/10.1007/978-3-319-91776-4_8
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